Tootfinder

Q&A with Yann LeCun on his new Paris-based startup Advanced Machine Intelligence, leaving Meta, real-world applications for world models, robotics, and more (Caiwei Chen/MIT Technology Review)
https://www.technologyreview.com/2026/01/22/1131661/yann-…

Yann LeCun’s new venture is a contrarian bet against large language models  
In an exclusive interview, the AI pioneer shares his plans for his new Paris-based company, AMI Labs.

AlertGuardian: Intelligent Alert Life-Cycle Management for Large-scale Cloud Systems
Guangba Yu, Genting Mai, Rui Wang, Ruipeng Li, Pengfei Chen, Long Pan, Ruijie Xu
https://arxiv.org/abs/2601.14912

The mastermind behind an extensive cyber-fraud empire, Vincent Chen Zhi, has been deported from Cambodia to China.
Cambodian tycoon Vincent Chen deported to China amid $10bn fraud and money laundering allegations | The Standard
https://www.thestandard.com.hk/china-news/article…

Cambodian tycoon Vincent Chen deported to China amid $10bn fraud and money laundering allegations
Vincent Chen Zhi, the founder and chairman of the Cambodian Prince Group, has been deported to China following his arrest in Cambodia amid serious allegations of large-scale fraud and money laundering, among other transnational crimes that involved more than US$10 billion.

And cue “Swiss neutrality” (privilege cowardice complicity) in 3… 2… @… https://hcommons.social/@adachika192/116087612441385859

Crosslisted article(s) found for cond-mat.dis-nn. https://arxiv.org/list/cond-mat.dis-nn/new
[1/1]:
- Realization of staircase topological Anderson phase transitions
Marwa Mannai, Yaoyao Shu, Sonia Haddad, Mina Ren, Hong Chen, Yong Sun, Hisham Sati

PAColorHolo: A Perceptually-Aware Color Management Framework for Holographic Displays
Chun Chen, Minseok Chae, Seung-Woo Nam, Myeong-Ho Choi, Minseong Kim, Eunbi Lee, Yoonchan Jeong, Jae-Hyeung Park
https://arxiv.org/abs/2601.14766 https://arxiv.org/pdf/2601.14766 https://arxiv.org/html/2601.14766
arXiv:2601.14766v1 Announce Type: new
Abstract: Holographic displays offer significant potential for augmented and virtual reality applications by reconstructing wavefronts that enable continuous depth cues and natural parallax without vergence-accommodation conflict. However, despite advances in pixel-level image quality, current systems struggle to achieve perceptually accurate color reproduction--an essential component of visual realism. These challenges arise from complex system-level distortions caused by coherent laser illumination, spatial light modulator imperfections, chromatic aberrations, and camera-induced color biases. In this work, we propose a perceptually-aware color management framework for holographic displays that jointly addresses input-output color inconsistencies through color space transformation, adaptive illumination control, and neural network-based perceptual modeling of the camera's color response. We validate the effectiveness of our approach through numerical simulations, optical experiments, and a controlled user study. The results demonstrate substantial improvements in perceptual color fidelity, laying the groundwork for perceptually driven holographic rendering in future systems.
toXiv_bot_toot

The Trump administration helps Tenet Media's Lauren Chen return to the US; she lost her visa after a 2024 indictment alleging illicit funding from Russia's RT (Will Sommer/The Bulwark)
https://www.thebulwark.com/p/lauren-chen-t

Trump Admin Scores Visa for Founder of Russian Propaganda Outlet
Tenet Media’s Lauren Chen is back—even though the illegal-influence and money-laundering investigation remains open.

I don't know what to make of this dispute: the toxic microplastics issue with artificial turf seems potentially real, but it's ridiculous that people are threatening to recall Chyanne Chen over it when she has basically no say in the matter.
https://missionlocal.org/2026/0…

It’s a (plastic) turf war at Crocker Amazon, and Chyanne Chen is caught in the middle
Anti-turf group says they’ll launch a recall of D11 Supervisor Chyanne Chen if Rec & Park and SF Giants plastic grass plan goes through.

Scam-Zentren: Kambodscha liefert mutmaßlichen Online-Betrüger nach China aus
Kambodscha hat den mutmaßlichen Online-Betrüger Chen Zhi ausgeliefert. Der Vorfall steht im Zusammenhang mit der Beschlagnahmung mehrerer Milliarden Bitcoins.

Crosslisted article(s) found for cs.DC. https://arxiv.org/list/cs.DC/new
[1/1]:
- Nixie: Efficient, Transparent Temporal Multiplexing for Consumer GPUs
Yechen Xu, Yifei Wang, Nathanael Ren, Yiran Chen, Danyang Zhuo

Replaced article(s) found for cs.OS. https://arxiv.org/list/cs.OS/new
[1/1]:
- Flare: Anomaly Diagnostics for Divergent LLM Training in GPU Clusters of Thousand-Plus Scale
Weihao Cui, Ji Zhang, Han Zhao, Chao Liu, Jian Sha, Bingsheng He, Minyi Guo, Quan Chen
https://arxiv.org/abs/2502.05413 https://mastoxiv.page/@arXiv_csOS_bot/113983966659919298
- Towards High-Goodput LLM Serving with Prefill-decode Multiplexing
Chen, Cui, Zhao, Xu, Fan, Chen, Zhou, Sun, He, Chen
https://arxiv.org/abs/2504.14489 https://mastoxiv.page/@arXiv_csOS_bot/114380402335312857
- Scaling Data Center TCP to Terabits with Laminar
Rajath Shashidhara, Antoine Kaufmann, Simon Peter
https://arxiv.org/abs/2504.19058 https://mastoxiv.page/@arXiv_csNI_bot/114420037697903281
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Towards Collinear Laser Spectroscopy of Radioactive Molecules Utilizing In-trap Produced Molecular Ion Beam
W. C. Mei, S. J. Chen, X. F. Yang, J. H. Lv, D. Y. Chen, H. R. Hu, Y. F. Guo, Z. Yan, Y. P. Jing, C. Zhang, Y. P. Lin, T. X. Gao, X. Shen, S. W. Bai, R. F. Garcia Ruiz, J. Yang, Y. L. Ye
https://arxiv.org/abs/2603.15533

Filing: Gemini says its COO, CFO, and chief legal officer are leaving; Cameron Winklevoss will take on many of the COO's duties; GEMI falls 10% (Olivier Acuna/CoinDesk)
https://www.coindesk.com/business/2026/02/

Gemini ousts COO, CFO and Chief Legal Officer after international exit and 25% staff cuts
Newly public crypto exchange Gemini Space Station Inc. said Marshall Beard, Dan Chen and Tyler Meade are departing effective immediately, days after the company announced plans to shut down U.K., EU and Australia operations and refocus on the U.S. and prediction markets.

Crosslisted article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- PointSLAM : Robust Dense Neural Gaussian Point Cloud-based SLAM
Xu Wang, Boyao Han, Xiaojun Chen, Ying Liu, Ruihui Li
https://arxiv.org/abs/2601.11617 https://mastoxiv.page/@arXiv_csCV_bot/115932177919726523
- Soft Shadow Diffusion (SSD): Physics-inspired Learning for 3D Computational Periscopy
Fadlullah Raji, John Murray-Bruce
https://arxiv.org/abs/2601.12257 https://mastoxiv.page/@arXiv_csCV_bot/115933514032062891
- NeuralFur: Animal Fur Reconstruction From Multi-View Images
Sklyarova, Kabadayi, Yiannakidis, Becherini, Black, Thies
https://arxiv.org/abs/2601.12481 https://mastoxiv.page/@arXiv_csCV_bot/115933577604103858
- Deep Feature Deformation Weights
Richard Liu, Itai Lang, Rana Hanocka
https://arxiv.org/abs/2601.12527 https://mastoxiv.page/@arXiv_csCV_bot/115933596082529002
- Criminator: An Easy-to-Use XR "Crime Animator" for Rapid Reconstruction and Analysis of Dynamic C...
Pooryousef, Besan\c{c}on, Cordeil, Flight, Ross, Bassed, Dwyer
https://arxiv.org/abs/2601.13689 https://mastoxiv.page/@arXiv_csHC_bot/115933503545993846
- Rig-Aware 3D Reconstruction of Vehicle Undercarriages using Gaussian Splatting
Kulkarni, Devarashetti, Cluss, Forte, Buckmaster, Schneider, Qiao, Vereshchaka
https://arxiv.org/abs/2601.14208 https://mastoxiv.page/@arXiv_csCV_bot/115933812616301038
toXiv_bot_toot

Im buddhistischen Tempel https://weddingweiser.de/im-buddhistischen-tempel/

Trump Admin Scores Visa for Founder of Russian Propaganda Outlet
https://www.thebulwark.com/p/lauren-chen-trump-administration-scores-visa-for-founder-russian-propaganda-outlet-tenet

Trump Admin Scores Visa for Founder of Russian Propaganda Outlet (Will Sommer/The Bulwark)
https://www.thebulwark.com/p/lauren-chen-trump-administration-scores-visa-for-founder-russian-propaganda-outlet-tenet
http://www.memeorandum.com/251229/p87#a251229p87

A look at the rise and fall of Chen Zhi, an alleged online scam kingpin whom the US and UK accused of laundering billions; he was extradited to China in January (Bloomberg)
https://www.bloomberg.com/news/features/20

Demonstration of High-Gain Harmonic Lasing in a Terahertz Free-Electron Laser
Yin Kang, Cheng Yu, Yue Wang, Weiyi Yin, Zhangfeng Gao, Hanghua Xu, Hang Luo, Jian Chen, Taihe Lan, Xiaoqing Liu, Jinguo Wang, Huan Zhao, Fei Gao, Liping Sun, YanYan Zhu, Yongmei Wen, Chengcheng Xiao, Yongfang Liu, Yixuan Liu, Xingtao Wang, Jiaqiang Xu, Zheng Qi, Tao Liu, Bin Li, Kaiqing Zhang, Zhen Wang, Chao Feng, Bo Liu, Zhentang Zhao
https://arxiv.org/abs/2602.13743 https://arxiv.org/pdf/2602.13743 https://arxiv.org/html/2602.13743
arXiv:2602.13743v1 Announce Type: new
Abstract: Compact Free-Electron Lasers (FELs) offering broad, continuous spectral tunability are traditionally constrained by fixed-parameter magnetic structures and the necessity for high-energy electron beams. High-gain Harmonic Lasing (HL) has long been proposed as a solution to overcome these limitations; however, a robust experimental verification of this principle has remained absent. Here, we report the first experimental demonstration of high-gain HL. By employing a frequency-tunable electron beam density modulation to dominate the fundamental instability, we achieved sustained FEL amplification at the 3rd and 5th harmonics of the wiggler. The HL mode generated output power comparable to conventional fundamental operation with enhanced stability and narrower spectral bandwidth. Notably, we demonstrate that HL extends the spectral coverage by a factor of two under fixed facility constraints, achieving pulse energies up to 540 {\mu}J. These results establish high-gain HL as a versatile mechanism for advancing compact, wavelength-flexible FEL facilities.
toXiv_bot_toot

The Fractional-Logarithmic Laplacian:Fundamental Properties and Eigenvalues
Huyuan Chen, Rui Chen, Daniel Hauer
https://arxiv.org/abs/2602.06581 https://ar…

Topological Anderson insulator and reentrant topological transitions in a mosaic trimer lattice
Xiatao Wang, Li Wang, Shu Chen
https://arxiv.org/abs/2601.13760 https://

Millimeter-scale rigid diamond probe for high sensitivity endoscopic-magnetometry applications
Jihongbo Shen, Heng Yuan, Hongyu Tao, Zekun Niu, Haoming Xu, Chentao Zhang, Chen Su, Zhuo Wang, Chen Zhang
https://arxiv.org/abs/2602.06077 https://arxiv.org/pdf/2602.06077 https://arxiv.org/html/2602.06077
arXiv:2602.06077v1 Announce Type: new
Abstract: Magnetometry based on diamond nitrogen-vacancy (NV) centers has been extensively studied for applications requiring diverse capabilities, spanning from nanometer spatial resolution to subpicotesla sensitivity. Among various applications, diamond magnetometers can demonstrate high sensitivity magnetic sensing within millimeter-scale size for endoscopic applications. However, the trade-off between sensitivity and spatial resolution of diamond magnetometry makes it difficult to achieve such a probe. In this study, we present a millimeter-scale rigid diamond magnetometer probe with enhanced sensitivity via optimizing the optical design. By coupling the frustum diamond with the miniaturized compound parabolic concentrator (CPC) lens, we enhance the fluorescence collection efficiency by 37% within 4 mm diameter, and the achieved sensitivity is 200 pT/Hz1/2 based on the sample with the resonance linewidth of ~8 MHz. With this verified structure, endoscopes with mm-size probe and picotesla sensitivity can be projected for surgical and industrial applications in the future.
toXiv_bot_toot

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/6]:
- Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang
https://arxiv.org/abs/2601.09708 https://mastoxiv.page/@arXiv_csCV_bot/115898618760721320
- Universality of Many-body Projected Ensemble for Learning Quantum Data Distribution
Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima
https://arxiv.org/abs/2601.18637 https://mastoxiv.page/@arXiv_quantph_bot/115967001797773134
- FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoning
Haozheng Luo, Zhuolin Jiang, Md Zahid Hasan, Yan Chen, Soumalya Sarkar
https://arxiv.org/abs/2601.19001 https://mastoxiv.page/@arXiv_csCL_bot/115972068838908815
- Analysis of Shuffling Beyond Pure Local Differential Privacy
Shun Takagi, Seng Pei Liew
https://arxiv.org/abs/2601.19154 https://mastoxiv.page/@arXiv_csDS_bot/115971701218309765
- CryoLVM: Self-supervised Learning from Cryo-EM Density Maps with Large Vision Models
Weining Fu, Kai Shu, Kui Xu, Qiangfeng Cliff Zhang
https://arxiv.org/abs/2602.02620
- XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas
Sultana, Afsar, Rahu, Singh, Shula, Combs, Forchetti, Asari
https://arxiv.org/abs/2602.04819
- Flow-Based Conformal Predictive Distributions
Trevor Harris
https://arxiv.org/abs/2602.07633 https://mastoxiv.page/@arXiv_statML_bot/116045671088130364
- GOT-Edit: Geometry-Aware Generic Object Tracking via Online Model Editing
Shih-Fang Chen, Jun-Cheng Chen, I-Hong Jhuo, Yen-Yu Lin
https://arxiv.org/abs/2602.08550 https://mastoxiv.page/@arXiv_csCV_bot/116046486984991360
- UI-Venus-1.5 Technical Report
Venus Team, et al.
https://arxiv.org/abs/2602.09082 https://mastoxiv.page/@arXiv_csCV_bot/116050980295461008
- The Wisdom of Many Queries: Complexity-Diversity Principle for Dense Retriever Training
Xincan Feng, Noriki Nishida, Yusuke Sakai, Yuji Matsumoto
https://arxiv.org/abs/2602.09448 https://mastoxiv.page/@arXiv_csIR_bot/116051022881293649
- Intent Laundering: AI Safety Datasets Are Not What They Seem
Shahriar Golchin, Marc Wetter
https://arxiv.org/abs/2602.16729 https://mastoxiv.page/@arXiv_csCR_bot/116101884238965526
- The Metaphysics We Train: A Heideggerian Reading of Machine Learning
Heman Shakeri
https://arxiv.org/abs/2602.19028 https://mastoxiv.page/@arXiv_csCY_bot/116125225694943789
- Skill-Inject: Measuring Agent Vulnerability to Skill File Attacks
David Schmotz, Luca Beurer-Kellner, Sahar Abdelnabi, Maksym Andriushchenko
https://arxiv.org/abs/2602.20156 https://mastoxiv.page/@arXiv_csCR_bot/116125330557447048
- A Very Big Video Reasoning Suite
Maijunxian Wang, et al.
https://arxiv.org/abs/2602.20159 https://mastoxiv.page/@arXiv_csCV_bot/116125664801070747
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Cambodia extradites Chen Zhi, the chairman of online scam conglomerate Prince Group, to China; in October, the US DOJ seized $12B in bitcoin belonging to Chen (Gabriele Steinhauser/Wall Street Journal)
https://www.wsj.com/world/asia/cambodian-s…

Replaced article(s) found for math.PR. https://arxiv.org/list/math.PR/new
[1/1]:
- On the free energy of vector spin glasses with non-convex interactions
Hong-Bin Chen, Jean-Christophe Mourrat

Finally the DSA SF Board of Supervisors scorecard is out ✨
The board passed a lot of terrible stuff last year, usually with Fielder and Walton in the minority (sometimes joined by Chan, Chen, or Melgar). I'm glad we have it on record with explanations. We're going to hold them accountable. A few good wins as well

2025 Board of Supervisors Voting Breakdown
In 2025, the San Francisco Board of Supervisors faced a defining set of choices about who this city is for. Again and again, a moderate supermajority supported increasing mayoral power, corporate i…

Direct Detection and Cosmological Constraints of Dark Matter with Dark Dipoles
Takumi Kuwahara, Jun-Chen Wang, Shu-Run Yuan
https://arxiv.org/abs/2602.06861 https://

Replaced article(s) found for q-bio.GN. https://arxiv.org/list/q-bio.GN/new
[1/1]:
- Partial domain adaptation enables cross domain cell type annotation between scRNA-seq and snRNA-seq
Xiran Chen, Quan Zou, Qinyu Cai, Xiaofeng Chen, Weikai Li, Yansu Wang

Pseudorotation and N-body Forces in an Optical Matter System
John Linderman, Shiqi Chen, Yanzeng Li, Alexandria Hoehn, Stuart A. Rice, Norbert F. Scherer
https://arxiv.org/abs/2602.11043

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Controllable Video Generation: A Survey
Ma, Feng, Hu, Wang, Wang, Zheng, He, Zhu, Liu, He, Wang, Li, Li, Liu, Xu, Zhang, Chen
https://arxiv.org/abs/2507.16869 https://mastoxiv.page/@arXiv_csGR_bot/114907178598354130
toXiv_bot_toot

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang
https://arxiv.org/abs/2411.09979 https://mastoxiv.page/@arXiv_csDS_bot/113502653187863544
- A Simple and Combinatorial Approach to Proving Chernoff Bounds and Their Generalizations
William Kuszmaul
https://arxiv.org/abs/2501.03488 https://mastoxiv.page/@arXiv_csDS_bot/113791396712128907
- The Structural Complexity of Matrix-Vector Multiplication
Emile Anand, Jan van den Brand, Rose McCarty
https://arxiv.org/abs/2502.21240 https://mastoxiv.page/@arXiv_csDS_bot/114097340825270885
- Clustering under Constraints: Efficient Parameterized Approximation Schemes
Sujoy Bhore, Ameet Gadekar, Tanmay Inamdar
https://arxiv.org/abs/2504.06980 https://mastoxiv.page/@arXiv_csDS_bot/114312444050875805
- Minimizing Envy and Maximizing Happiness in Graphical House Allocation
Anubhav Dhar, Ashlesha Hota, Palash Dey, Sudeshna Kolay
https://arxiv.org/abs/2505.00296 https://mastoxiv.page/@arXiv_csDS_bot/114437013364446063
- Fast and Simple Densest Subgraph with Predictions
Thai Bui, Luan Nguyen, Hoa T. Vu
https://arxiv.org/abs/2505.12600 https://mastoxiv.page/@arXiv_csDS_bot/114538936921930134
- Compressing Suffix Trees by Path Decompositions
Becker, Cenzato, Gagie, Kim, Koerkamp, Manzini, Prezza
https://arxiv.org/abs/2506.14734 https://mastoxiv.page/@arXiv_csDS_bot/114703384646892523
- Improved sampling algorithms and functional inequalities for non-log-concave distributions
Yuchen He, Zhehan Lei, Jianan Shao, Chihao Zhang
https://arxiv.org/abs/2507.11236 https://mastoxiv.page/@arXiv_csDS_bot/114862112197588124
- Deterministic Lower Bounds for $k$-Edge Connectivity in the Distributed Sketching Model
Peter Robinson, Ming Ming Tan
https://arxiv.org/abs/2507.11257 https://mastoxiv.page/@arXiv_csDS_bot/114862223634372292
- Optimally detecting uniformly-distributed $\ell_2$ heavy hitters in data streams
Santhoshini Velusamy, Huacheng Yu
https://arxiv.org/abs/2509.07286 https://mastoxiv.page/@arXiv_csDS_bot/115178875220889588
- Uncrossed Multiflows and Applications to Disjoint Paths
Chandra Chekuri, Guyslain Naves, Joseph Poremba, F. Bruce Shepherd
https://arxiv.org/abs/2511.00254 https://mastoxiv.page/@arXiv_csDS_bot/115490402963680492
- Dynamic Matroids: Base Packing and Covering
Tijn de Vos, Mara Grilnberger
https://arxiv.org/abs/2511.15460 https://mastoxiv.page/@arXiv_csDS_bot/115580946319285096
- Branch-width of connectivity functions is fixed-parameter tractable
Tuukka Korhonen, Sang-il Oum
https://arxiv.org/abs/2601.04756 https://mastoxiv.page/@arXiv_csDS_bot/115864074799755995
- CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman
https://arxiv.org/abs/2006.06618
- The Ideal Membership Problem and Abelian Groups
Andrei A. Bulatov, Akbar Rafiey
https://arxiv.org/abs/2201.05218
- Bridging Classical and Quantum: Group-Theoretic Approach to Quantum Circuit Simulation
Daksh Shami
https://arxiv.org/abs/2407.19575 https://mastoxiv.page/@arXiv_quantph_bot/112874282709517475
- Young domination on Hamming rectangles
Janko Gravner, Matja\v{z} Krnc, Martin Milani\v{c}, Jean-Florent Raymond
https://arxiv.org/abs/2501.03788 https://mastoxiv.page/@arXiv_mathCO_bot/113791421814248215
- On the Space Complexity of Online Convolution
Joel Daniel Andersson, Amir Yehudayoff
https://arxiv.org/abs/2505.00181 https://mastoxiv.page/@arXiv_csCC_bot/114437005955255553
- Universal Solvability for Robot Motion Planning on Graphs
Anubhav Dhar, Pranav Nyati, Tanishq Prasad, Ashlesha Hota, Sudeshna Kolay
https://arxiv.org/abs/2506.18755 https://mastoxiv.page/@arXiv_csCC_bot/114737342714568702
- Colorful Minors
Evangelos Protopapas, Dimitrios M. Thilikos, Sebastian Wiederrecht
https://arxiv.org/abs/2507.10467
- Learning fermionic linear optics with Heisenberg scaling and physical operations
Aria Christensen, Andrew Zhao
https://arxiv.org/abs/2602.05058
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Crosslisted article(s) found for cs.FL. https://arxiv.org/list/cs.FL/new
[1/1]:
- ToolGate: Contract-Grounded and Verified Tool Execution for LLMs
Liu, Peng, Cao, Wang, Deng, Chen, Yin, Zhang
https://arxiv.org/abs/2601.04688 https://mastoxiv.page/@arXiv_csCL_bot/115864682235226314
- Generalised Quantifiers Based on Rabin-Mostowski Index
Denis Kuperberg, Damian Niwi\'nski, Pawe{\l} Parys, Micha{\l} Skrzypczak
https://arxiv.org/abs/2601.04739 https://mastoxiv.page/@arXiv_csLO_bot/115864230064408440
toXiv_bot_toot

62 people indicted by Taiwanese prosecutors over ties to cyber scam company Prince Group https://therecord.media/62-indicted-taiwan-prince-group-scams

Physics-informed neural networks for solving strong-field saddle-point equations in strong-field physics with tailored fields
Jiakang Chen, Sufia Hashim, Carla Figueira de Morisson Faria
https://arxiv.org/abs/2603.15786

Millimeter-scale rigid diamond probe for high sensitivity endoscopic-magnetometry applications
Jihongbo Shen, Heng Yuan, Hongyu Tao, Zekun Niu, Haoming Xu, Chentao Zhang, Chen Su, Zhuo Wang, Chen Zhang
https://arxiv.org/abs/2602.06077

A small cottage industry offering OpenClaw installation services and preconfigured hardware emerges in China as the tool becomes the country's latest tech craze (Caiwei Chen/MIT Technology Review)
https://www.technologyreview.com/2026/03/11/1134179/china-ope…

Hustlers are cashing in on China’s OpenClaw AI craze
The AI tool has become the country's latest tech obsession. For savvy early adopters, that's a business opportunity.

Democratic Governors Promise Accountability After Minneapolis (David W. Chen/New York Times)
https://www.nytimes.com/2026/01/29/us/politics/democrats-governors-trump-minneapolis.html
http://www.memeorandum.com/260129/p87#a260129p87

Towards Autonomous Graph Data Analytics with Analytics-Augmented Generation
Qiange Wang, Chaoyi Chen, Jingqi Gao, Zihan Wang, Yanfeng Zhang, Ge Yu
https://arxiv.org/abs/2602.21604

Orbital Magnetization of Interacting Electrons
Xi Chen, Zhi-Da Song
https://arxiv.org/abs/2602.02478 https://arxiv.org/pdf/2602.02478

Intelligent Control of Transportation Flow in Physarum Networks
Bingyang Han, Luolan Chen, Tieyan Si
https://arxiv.org/abs/2602.00200 https://arxiv.org/pdf…

Chiral phase transition with primordial black holes: Distinct phase structure and catalysis
Masanori Tanaka, Jun-Chen Wang, Jing-Jun Zhang
https://arxiv.org/abs/2602.06661 https…

Linear thermal noise induced by Berry curvature dipole in a four-terminal system
Wenyu Chen, Miaomiao Wei, Yunjin Yu, Fuming Xu, Jian Wang
https://arxiv.org/abs/2602.10406 https…

Malwarebytes: a 2024 Instagram data breach exposed information on 17.5 million users, including emails, phone numbers, and physical addresses (Jackson Chen/Engadget)
https://www.engadget.com/cybersecurity/an-

An Instagram data breach reportedly exposed the personal info of 17.5 million users
The leak may be responsible for Instagram users receiving plenty of emails requesting a password reset.

Remainder terms and sharp quantitative stability for a nonlocal Sobolev inequality on the Heisenberg group
Wenjing Chen, Zexi Wang
https://arxiv.org/abs/2602.08375 https://

UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Wei Chen, Yuqian Wu, Junle Chen, Xiaofang Zhou, Yuxuan Liang
https://arxiv.org/abs/2602.20677 https://arxiv.org/pdf/2602.20677 https://arxiv.org/html/2602.20677
arXiv:2602.20677v1 Announce Type: new
Abstract: Urban systems, as dynamic complex systems, continuously generate spatio-temporal data streams that encode the fundamental laws of human mobility and city evolution. While AI for Science has witnessed the transformative power of foundation models in disciplines like genomics and meteorology, urban computing remains fragmented due to "scenario-specific" models, which are overfitted to specific regions or tasks, hindering their generalizability. To bridge this gap and advance spatio-temporal foundation models for urban systems, we adopt scaling as the central perspective and systematically investigate two key questions: what to scale and how to scale. Grounded in first-principles analysis, we identify three critical dimensions: heterogeneity, correlation, and dynamics, aligning these principles with the fundamental scientific properties of urban spatio-temporal data. Specifically, to address heterogeneity through data scaling, we construct WorldST. This billion-scale corpus standardizes diverse physical signals, such as traffic flow and speed, from over 100 global cities into a unified data format. To enable computation scaling for modeling correlations, we introduce the MiniST unit, a novel split mechanism that discretizes continuous spatio-temporal fields into learnable computational units to unify representations of grid-based and sensor-based observations. Finally, addressing dynamics via architecture scaling, we propose UrbanFM, a minimalist self-attention architecture designed with limited inductive biases to autonomously learn dynamic spatio-temporal dependencies from massive data. Furthermore, we establish EvalST, the largest-scale urban spatio-temporal benchmark to date. Extensive experiments demonstrate that UrbanFM achieves remarkable zero-shot generalization across unseen cities and tasks, marking a pivotal first step toward large-scale urban spatio-temporal foundation models.
toXiv_bot_toot

Closed-loop dual-channel atomic beam interferometry beyond the half-fringe limit
Wei-Chen Jia, Yue Xin, Ke Shen, Zhi-Xin Meng, Xiang-Xiang Lu, Yi-Cheng Deng, Yuan-Xing Liu, Yan-Ying Feng
https://arxiv.org/abs/2603.14777

Replaced article(s) found for cs.OS. https://arxiv.org/list/cs.OS/new
[1/1]:
- Sharpen the Spec, Cut the Code: A Case for Generative File System with SYSSPEC
Qingyuan Liu, Mo Zou, Hengbin Zhang, Dong Du, Yubin Xia, Haibo Chen
https://arxiv.org/abs/2512.13047 https://mastoxiv.page/@arXiv_csOS_bot/115728274713378897
- Selective KV-Cache Sharing to Mitigate Timing Side-Channels in LLM Inference
Chu, Lin, Xiang, Shen, Su, Chu, Yang, Zhang, Wu, Zhang
https://arxiv.org/abs/2508.08438 https://mastoxiv.page/@arXiv_csCR_bot/115020390232560161
- Hazel: Secure and Efficient Disaggregated Storage
Chrapek, Orenbach, Atamli, Copik, Khalilov, Alder, Hoefler
https://arxiv.org/abs/2510.18756 https://mastoxiv.page/@arXiv_csCR_bot/115417285313341172
toXiv_bot_toot

Crosslisted article(s) found for nlin.PS. https://arxiv.org/list/nlin.PS/new
[1/1]:
- Multi-ring necklace vortex solitons in Kerr nonlinear media with azimuthally modulated Bessel pot...
Ruolan Zhao, Jing Chen, Boris A. Malomed, Rongcao Yang
https://arxiv.org/abs/2602.18703 https://mastoxiv.page/@arXiv_physicsoptics_bot/116124716293004310
- Superflows around corners
Thomas Frisch, Christophe Josserand, Sergio Rica
https://arxiv.org/abs/2602.18876 https://mastoxiv.page/@arXiv_condmatquantgas_bot/116124612627245203
toXiv_bot_toot

Replaced article(s) found for math.DG. https://arxiv.org/list/math.DG/new
[1/1]:
- On the modified $J$-equation
Ryosuke Takahashi
https://arxiv.org/abs/2207.04953
- Surfaces with flat normal connection in 4-dimensional space forms
Naoya Ando, Ryusei Hatanaka
https://arxiv.org/abs/2501.15780
- Regularized $\zeta_{\Delta}(1)$ for Polyhedra
Alexey Yu. Kokotov, Dmitrii V. Korikov
https://arxiv.org/abs/2502.03351 https://mastoxiv.page/@arXiv_mathDG_bot/113955669526276293
- General Chen-Ricci inequalities for Riemannian submersions and Riemannian maps
Ravindra Singh, Kiran Meena, Kapish Chand Meena
https://arxiv.org/abs/2509.15281 https://mastoxiv.page/@arXiv_mathDG_bot/115246828823405190
- Some configuration results for area-minimizing cones
Yongsheng Zhang
https://arxiv.org/abs/2510.17240 https://mastoxiv.page/@arXiv_mathDG_bot/115411416287934120
- Real Bers embedding on the line: Fisher-Rao linearization, Schwarzian curvature, and scattering c...
Hy Lam
https://arxiv.org/abs/2602.07373 https://mastoxiv.page/@arXiv_mathDG_bot/116045447030638429
- Explicit Hamiltonian representations of meromorphic connections and duality from different perspe...
Mohamad Alameddine, Olivier Marchal
https://arxiv.org/abs/2406.19187 https://mastoxiv.page/@arXiv_mathph_bot/112692974532066693
- An alternative solvability criterion for the Dirichlet problem for the minimal surface equation a...
Ari J. Aiolfi, Giovanni da Silva Nunes, Jaime Ripoll, Lisandra Sauer, Rodrigo Soares
https://arxiv.org/abs/2508.09806 https://mastoxiv.page/@arXiv_mathAP_bot/115026282591071982
- Gromov's Compactness Theorem for the Intrinsic Timed-Hausdorff Distance
Mauricio Che, Raquel Perales, Christina Sormani
https://arxiv.org/abs/2510.13069 https://mastoxiv.page/@arXiv_mathMG_bot/115382835673596437
- Nearly optimal spectral gaps for random Belyi surfaces
Yang Shen, Yunhui Wu
https://arxiv.org/abs/2511.02517 https://mastoxiv.page/@arXiv_mathSP_bot/115496082425305449
toXiv_bot_toot

Replaced article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
- Flow birefringence measurement in a radial Hele-Shaw cell considering three-dimensional effects
Kawaguchi, Worby, Yokoyama, Suzuki, Nagatsu, Tagawa
https://arxiv.org/abs/2503.10261 https://mastoxiv.page/@arXiv_physicsfludyn_bot/114159626474808492
- Harnessing natural and mechanical airflows for surface-based atmospheric pollutant removal
Tomlinson, Tsopelakou, Onn, Barrett, Boies, Fitzgerald
https://arxiv.org/abs/2503.11803 https://mastoxiv.page/@arXiv_physicsfludyn_bot/114182280989424086
- Modelling laminar flow in V-shaped filters integrated with catalyst technologies for atmospheric ...
Tomlinson, Tsopelakou, Onn, Barrett, Boies, Fitzgerald
https://arxiv.org/abs/2506.00603 https://mastoxiv.page/@arXiv_physicsfludyn_bot/114618363713267810
- Physics-based modelling of turbulence in wind-turbine wakes turbulence in neutral atmospheric bou...
Fr\'ed\'eric Blondel, Erwan J\'ez\'equel, Helen Schottenhamml, Majid Bastankhah
https://arxiv.org/abs/2508.20012 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115105574493910598
- Laminar boundary layers over small-scale textured surfaces
Samuel D. Tomlinson, Demetrios T. Papageorgiou
https://arxiv.org/abs/2511.11471 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115564297614664642
- Tensor Network Lattice Boltzmann Method for Data-Compressed Fluid Simulations
Lukas Gross, Elie Mounzer, David M. Wawrzyniak, Josef M. Winter, Nikolaus A. Adams
https://arxiv.org/abs/2512.07615 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115689326375361321
- Low Regularity of Self-Similar Solutions of Two-Dimensional Riemann problems with Shocks for the ...
Gui-Qiang G. Chen, Mikhail Feldman, Wei Xiang
https://arxiv.org/abs/2504.07034 https://mastoxiv.page/@arXiv_mathAP_bot/114312466798796116
toXiv_bot_toot

Crosslisted article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Graph-Based Nearest-Neighbor Search without the Spread
Jeff Giliberti, Sariel Har-Peled, Jonas Sauer, Ali Vakilian
https://arxiv.org/abs/2602.06633 https://mastoxiv.page/@arXiv_csCG_bot/116039510003959758
- Tensor Hinted Mv Conjectures
Zhao Song
https://arxiv.org/abs/2602.07242 https://mastoxiv.page/@arXiv_csCC_bot/116045166832661818
- Compact Conformal Subgraphs
Sreenivas Gollapudi, Kostas Kollias, Kamesh Munagala, Aravindan Vijayaraghavan
https://arxiv.org/abs/2602.07530 https://mastoxiv.page/@arXiv_csLG_bot/116046310688959095
- The Parameterized Complexity of Independent Set and More when Excluding a Half-Graph, Co-Matching...
Jan Dreier, Nikolas M\"ahlmann, Sebastian Siebertz
https://arxiv.org/abs/2602.07606 https://mastoxiv.page/@arXiv_csCC_bot/116045172877973476
- A Two-Layer Framework for Joint Online Configuration Selection and Admission Control
Owen Shen, Haoran Xu, Yinyu Ye, Peter Glynn, Patrick Jaillet
https://arxiv.org/abs/2602.07663 https://mastoxiv.page/@arXiv_mathOC_bot/116046008531918566
- Efficient Adaptive Data Analysis over Dense Distributions
Joon Suk Huh
https://arxiv.org/abs/2602.07732 https://mastoxiv.page/@arXiv_csLG_bot/116046380158677039
- Wheeler Bisimulations
Nicola Cotumaccio
https://arxiv.org/abs/2602.07964 https://mastoxiv.page/@arXiv_csFL_bot/116045203254419984
- Trellis codes with a good distance profile constructed from expander graphs
Yubin Zhu, Zitan Chen
https://arxiv.org/abs/2602.08718 https://mastoxiv.page/@arXiv_csIT_bot/116046151403913561
- Near-optimal Swap Regret Minimization for Convex Losses
Lunjia Hu, Jon Schneider, Yifan Wu
https://arxiv.org/abs/2602.08862 https://mastoxiv.page/@arXiv_csLG_bot/116046574152052711
- Distortion of Metric Voting with Bounded Randomness
Ziyi Cai, D. D. Gao, Prasanna Ramakrishnan, Kangning Wang
https://arxiv.org/abs/2602.08871 https://mastoxiv.page/@arXiv_csGT_bot/116045826992016756
toXiv_bot_toot

Quasiperiodicity-induced non-Hermitian skin effect from the breakdown of scale-free localization
Kazuma Saito, Ryo Okugawa, Kazuki Yokomizo, Takami Tohyama, Chen-Hsuan Hsu
https://arxiv.org/abs/2602.11155

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Enhanced multi-parameter metrology in dissipative Rydberg atom time crystals
Liu, Chen, Ma, Wang, Han, Tian, Qian, Guo, Zhang, Wei, Bayat, Ding, Shi

Detecting Logic Bugs of Join Optimizations in DBMS
Xiu Tang, Sai Wu, Dongxiang Zhang, Feifei Li, Gang Chen
https://arxiv.org/abs/2602.21955 https://arxiv.o…

Van Hove singularity-induced multiple magnetic transitions in multi-orbital systems
Chen Lu, Lun-Hui Hu
https://arxiv.org/abs/2602.00698 https://arxiv.org/…

A look at the US DOJ's December lawsuit alleging a smuggling ring illegally exported or tried to export at least $160M in advanced Nvidia AI chips to China (Eliot Chen/The Wire China)
https://www.thewirechina.com/2026/03/01/chasing-the-chip-smugg…

Chasing the Chip Smugglers - The Wire China
The exposure of a U.S.-based operation that smuggled Nvidia’s AI chips to China raises questions about the role of major companies and the authorities charged with enforcing export controls.

Crosslisted article(s) found for physics.ins-det. https://arxiv.org/list/physics.ins-det/new
[1/1]:
- U-Net Based Image Enhancement for Short-time Muon Scattering Tomography
Wang, Yu, Chen, He, Zhang, Yu, Zhang, Yang, Sun

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Locality-Aware Automatic Differentiation on the GPU for Mesh-Based Computations
Ahmed H. Mahmoud, Rahul Goel, Jonathan Ragan-Kelley, Justin Solomon
https://arxiv.org/abs/2509.00406 https://mastoxiv.page/@arXiv_csGR_bot/115139432473803894
- F-scheduler: illuminating the free-lunch design space for fast sampling of diffusion models
Zilai Li, Lujia Bai
https://arxiv.org/abs/2510.02390 https://mastoxiv.page/@arXiv_csGR_bot/115326072853284835
- Mesh Splatting for End-to-end Multiview Surface Reconstruction
Ruiqi Zhang, Jiacheng Wu, Jie Chen
https://arxiv.org/abs/2601.21400 https://mastoxiv.page/@arXiv_csGR_bot/115983057390044475
- InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions
Sirui Xu, Hung Yu Ling, Yu-Xiong Wang, Liang-Yan Gui
https://arxiv.org/abs/2502.20390 https://mastoxiv.page/@arXiv_csCV_bot/114080380833806621
- Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerate...
Zhaowen Fan
https://arxiv.org/abs/2601.06135 https://mastoxiv.page/@arXiv_csLG_bot/115887382327150666
- Under-Canopy Terrain Reconstruction in Dense Forests Using RGB Imaging and Neural 3D Reconstruction
Refael Sheffer, Chen Pinchover, Haim Zisman, Dror Ozeri, Roee Litman
https://arxiv.org/abs/2601.22861 https://mastoxiv.page/@arXiv_csCV_bot/116000605470776021
toXiv_bot_toot

Broadband Heterodyne Microwave Detection using Rydberg Atoms with High Sensitivity
Hsuan-Jui Su, Shao-Cheng Fang, Ting-An Li, Chen-Hao Chang, Yu-Chi Chen, Yi-Hsin Chen
https://arxiv.org/abs/2601.19305 …

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/6]:
- Towards Scalable Oversight via Partitioned Human Supervision
Ren Yin, Takashi Ishida, Masashi Sugiyama
https://arxiv.org/abs/2510.22500 https://mastoxiv.page/@arXiv_csLG_bot/115451787490434401
- ContextPilot: Fast Long-Context Inference via Context Reuse
Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
https://arxiv.org/abs/2511.03475 https://mastoxiv.page/@arXiv_csLG_bot/115502245581974540
- Metabolomic Biomarker Discovery for ADHD Diagnosis Using Interpretable Machine Learning
Nabil Belacel, Mohamed Rachid Boulassel
https://arxiv.org/abs/2601.11283 https://mastoxiv.page/@arXiv_csLG_bot/115921183182326799
- PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction
Akila Sampath, Vandana Janeja, Jianwu Wang
https://arxiv.org/abs/2601.17074
- SAGE-5GC: Security-Aware Guidelines for Evaluating Anomaly Detection in the 5G Core Network
Cristian Manca, Christian Scano, Giorgio Piras, Fabio Brau, Maura Pintor, Battista Biggio
https://arxiv.org/abs/2602.03596
- LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordina...
Anand, Helbling, Davenport, Berman, Alagapan, Rozell
https://arxiv.org/abs/2602.04192
- Towards Robust Scaling Laws for Optimizers
Alexandra Volkova, Mher Safaryan, Christoph H. Lampert, Dan Alistarh
https://arxiv.org/abs/2602.07712 https://mastoxiv.page/@arXiv_csLG_bot/116046369672796465
- Do We Need Adam? Surprisingly Strong and Sparse Reinforcement Learning with SGD in LLMs
Sagnik Mukherjee, Lifan Yuan, Pavan Jayasinha, Dilek Hakkani-T\"ur, Hao Peng
https://arxiv.org/abs/2602.07729 https://mastoxiv.page/@arXiv_csLG_bot/116046377539155485
- AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine L...
Yuzhu Cai, Zexi Liu, Xinyu Zhu, Cheng Wang, Siheng Chen
https://arxiv.org/abs/2602.07906 https://mastoxiv.page/@arXiv_csLG_bot/116046423413650658
- VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Guobin Shen, Chenxiao Zhao, Xiang Cheng, Lei Huang, Xing Yu
https://arxiv.org/abs/2602.10693 https://mastoxiv.page/@arXiv_csLG_bot/116057229834947730
- KBVQ-MoE: KLT-guided SVD with Bias-Corrected Vector Quantization for MoE Large Language Models
Zukang Xu, Zhixiong Zhao, Xing Hu, Zhixuan Chen, Dawei Yang
https://arxiv.org/abs/2602.11184 https://mastoxiv.page/@arXiv_csLG_bot/116062537528208461
- MUSE: Multi-Tenant Model Serving With Seamless Model Updates
Correia, Ferreira, Martins, Bento, Guerreiro, Pereira, Gomes, Bono, Ferreira, Bizarro
https://arxiv.org/abs/2602.11776 https://mastoxiv.page/@arXiv_csLG_bot/116062952355379801
- Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
Jorge Carrasco-Pollo, Floor Eijkelboom, Jan-Willem van de Meent
https://arxiv.org/abs/2602.13813 https://mastoxiv.page/@arXiv_csLG_bot/116085828112928218
- Silent Inconsistency in Data-Parallel Full Fine-Tuning: Diagnosing Worker-Level Optimization Misa...
Hong Li, Zhen Zhou, Honggang Zhang, Yuping Luo, Xinyue Wang, Han Gong, Zhiyuan Liu
https://arxiv.org/abs/2602.14462 https://mastoxiv.page/@arXiv_csLG_bot/116085997857526328
- Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs
Alejandro Francisco Queiruga
https://arxiv.org/abs/2602.14495 https://mastoxiv.page/@arXiv_csLG_bot/116086011618741857
- \"UberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset
DatologyAI, et al.
https://arxiv.org/abs/2602.15210 https://mastoxiv.page/@arXiv_csLG_bot/116090912256712568
- GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, et al.
https://arxiv.org/abs/2602.15763 https://mastoxiv.page/@arXiv_csLG_bot/116091080686771018
- Anatomy of Capability Emergence: Scale-Invariant Representation Collapse and Top-Down Reorganizat...
Jayadev Billa
https://arxiv.org/abs/2602.15997 https://mastoxiv.page/@arXiv_csLG_bot/116096541546306333
- AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
KC Santosh, Srikanth Baride, Rodrigue Rizk
https://arxiv.org/abs/2602.16042 https://mastoxiv.page/@arXiv_csLG_bot/116096581524696028
- Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
Chuqin Geng, Li Zhang, Haolin Ye, Ziyu Zhao, Yuhe Jiang, Tara Saba, Xinyu Wang, Xujie Si
https://arxiv.org/abs/2602.16947 https://mastoxiv.page/@arXiv_csLG_bot/116102426238903124
toXiv_bot_toot

Sources: ByteDance plans to spend about $14B on Nvidia's AI chips in 2026, an increase of about 18% from 2025 (Wency Chen/South China Morning Post)
https://www.scmp.com/tech/big-tech/article/3338191/bytedance-pour-u…

Exclusive | ByteDance to pour US$14 billion into Nvidia chips in 2026 as AI demand surges
Chinese unicorn’s computing needs have climbed across its portfolio of popular apps, cloud unit Volcano Engine and large language models.

ProphetKV: User-Query-Driven Selective Recomputation for Efficient KV Cache Reuse in Retrieval-Augmented Generation
Shihao Wang, Jiahao Chen, Yanqi Pan, Hao Huang, Yichen Hao, Xiangyu Zou, Wen Xia, Wentao Zhang, Haitao Wang, Junhong Li, Chongyang Qiu, Pengfei Wang
https://arxiv.org/abs/2602.02579 https://arxiv.org/pdf/2602.02579 https://arxiv.org/html/2602.02579
arXiv:2602.02579v1 Announce Type: new
Abstract: The prefill stage of long-context Retrieval-Augmented Generation (RAG) is severely bottlenecked by computational overhead. To mitigate this, recent methods assemble pre-calculated KV caches of retrieved RAG documents (by a user query) and reprocess selected tokens to recover cross-attention between these pre-calculated KV caches. However, we identify a fundamental "crowding-out effect" in current token selection criteria: globally salient but user-query-irrelevant tokens saturate the limited recomputation budget, displacing the tokens truly essential for answering the user query and degrading inference accuracy.
We propose ProphetKV, a user-query-driven KV Cache reuse method for RAG scenarios. ProphetKV dynamically prioritizes tokens based on their semantic relevance to the user query and employs a dual-stage recomputation pipeline to fuse layer-wise attention metrics into a high-utility set. By ensuring the recomputation budget is dedicated to bridging the informational gap between retrieved context and the user query, ProphetKV achieves high-fidelity attention recovery with minimal overhead. Our extensive evaluation results show that ProphetKV retains 96%-101% of full-prefill accuracy with only a 20% recomputation ratio, while achieving accuracy improvements of 8.8%-24.9% on RULER and 18.6%-50.9% on LongBench over the state-of-the-art approaches (e.g., CacheBlend, EPIC, and KVShare).
toXiv_bot_toot

RAC: Relation-Aware Cache Replacement for Large Language Models
Yuchong Wu, Zihuan Xu, Wangze Ni, Peng Cheng, Lei Chen, Xuemin Lin, Heng Tao Shen, Kui Ren
https://arxiv.org/abs/2602.21547

Reexamining the strange metal charge response with transmission inelastic electron scattering
Niels de Vries, Eric Hoglund, Dipanjan Chaudhuri, Sang hyun Bae, Jin Chen, Xuefei Guo, David Balut, Genda Gu, Pinshane Huang, Jordan Hachtel, Peter Abbamonte
https://arxiv.org/abs/2602.02348

Synthetic Gauge Phase in Rydberg Electromagnetically Induced Transparency
Ya-Dong Hu, Yi-Chen Zhang, Qing-Xuan Jie, Hong-Jie Fan, Xiao-Kang Zhong, Dong-Qi Ma, Ya-Nan Lv, Yan-Lei Zhang, Xu-Bo Zou, Song-Bai Kang, Guang-Can Guo, Zhu-Bo Wang, Chang-Ling Zou
https://arxiv.org/abs/2602.11682

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/6]:
- Towards Attributions of Input Variables in a Coalition
Xinhao Zheng, Huiqi Deng, Quanshi Zhang
https://arxiv.org/abs/2309.13411
- Knee or ROC
Veronica Wendt, Jacob Steiner, Byunggu Yu, Caleb Kelly, Justin Kim
https://arxiv.org/abs/2401.07390
- Rethinking Disentanglement under Dependent Factors of Variation
Antonio Almud\'evar, Alfonso Ortega
https://arxiv.org/abs/2408.07016 https://mastoxiv.page/@arXiv_csLG_bot/112959235461894530
- Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
Etrit Haxholli, Yeti Z. Gurbuz, Ogul Can, Eli Waxman
https://arxiv.org/abs/2411.00759 https://mastoxiv.page/@arXiv_csLG_bot/113423933393275133
- Predicting Subway Passenger Flows under Incident Situation with Causality
Xiannan Huang, Shuhan Qiu, Quan Yuan, Chao Yang
https://arxiv.org/abs/2412.06871 https://mastoxiv.page/@arXiv_csLG_bot/113632934357523592
- Characterizing LLM Inference Energy-Performance Tradeoffs across Workloads and GPU Scaling
Paul Joe Maliakel, Shashikant Ilager, Ivona Brandic
https://arxiv.org/abs/2501.08219 https://mastoxiv.page/@arXiv_csLG_bot/113831081884570770
- Universality of Benign Overfitting in Binary Linear Classification
Ichiro Hashimoto, Stanislav Volgushev, Piotr Zwiernik
https://arxiv.org/abs/2501.10538 https://mastoxiv.page/@arXiv_csLG_bot/113872351652969955
- Safe Reinforcement Learning for Real-World Engine Control
Julian Bedei, Lucas Koch, Kevin Badalian, Alexander Winkler, Patrick Schaber, Jakob Andert
https://arxiv.org/abs/2501.16613 https://mastoxiv.page/@arXiv_csLG_bot/113910356206562660
- A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers
Roman Tarasov, Petr Mokrov, Milena Gazdieva, Evgeny Burnaev, Alexander Korotin
https://arxiv.org/abs/2502.01310
- Improving the Convergence of Private Shuffled Gradient Methods with Public Data
Shuli Jiang, Pranay Sharma, Zhiwei Steven Wu, Gauri Joshi
https://arxiv.org/abs/2502.03652 https://mastoxiv.page/@arXiv_csLG_bot/113961314098841096
- Using the Path of Least Resistance to Explain Deep Networks
Sina Salek, Joseph Enguehard
https://arxiv.org/abs/2502.12108 https://mastoxiv.page/@arXiv_csLG_bot/114023706252106865
- Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence
Wenzhe Yin, Zehao Xiao, Pan Zhou, Shujian Yu, Jiayi Shen, Jan-Jakob Sonke, Efstratios Gavves
https://arxiv.org/abs/2502.17028 https://mastoxiv.page/@arXiv_csLG_bot/114063477202397951
- Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
https://arxiv.org/abs/2503.00229 https://mastoxiv.page/@arXiv_csLG_bot/114103018985567633
- Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
Yan Li, Zhenyu Zhang, Zhengang Wang, Pengfei Chen, Pengfei Zheng
https://arxiv.org/abs/2503.04398 https://mastoxiv.page/@arXiv_csLG_bot/114120014622063602
- A Survey on Federated Fine-tuning of Large Language Models
Wu, Tian, Li, Sun, Tam, Zhou, Liao, Xiong, Guo, Li, Xu
https://arxiv.org/abs/2503.12016 https://mastoxiv.page/@arXiv_csLG_bot/114182234054681647
- Towards Trustworthy GUI Agents: A Survey
Yucheng Shi, Wenhao Yu, Jingyuan Huang, Wenlin Yao, Wenhu Chen, Ninghao Liu
https://arxiv.org/abs/2503.23434 https://mastoxiv.page/@arXiv_csLG_bot/114263024618476521
- CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee
Chao Yang, Xiannan Huang, Shuhan Qiu, Yan Cheng
https://arxiv.org/abs/2504.13961 https://mastoxiv.page/@arXiv_csLG_bot/114380404041503229
- Regularity and Stability Properties of Selective SSMs with Discontinuous Gating
Nikola Zubi\'c, Davide Scaramuzza
https://arxiv.org/abs/2505.11602 https://mastoxiv.page/@arXiv_csLG_bot/114538965060456498
- RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization
Alonso Urbano, David W. Romero, Max Zimmer, Sebastian Pokutta
https://arxiv.org/abs/2505.13289 https://mastoxiv.page/@arXiv_csLG_bot/114539124884913788
- RefLoRA: Refactored Low-Rank Adaptation for Efficient Fine-Tuning of Large Models
Yilang Zhang, Bingcong Li, Georgios B. Giannakis
https://arxiv.org/abs/2505.18877 https://mastoxiv.page/@arXiv_csLG_bot/114578778213033886
- SuperMAN: Interpretable and Expressive Networks over Temporally Sparse Heterogeneous Data
Bechler-Speicher, Zerio, Huri, Vestergaard, Gilad-Bachrach, Jess, Bhatt, Sazonovs
https://arxiv.org/abs/2505.19193 https://mastoxiv.page/@arXiv_csLG_bot/114578790124778172
toXiv_bot_toot

Replaced article(s) found for cs.OS. https://arxiv.org/list/cs.OS/new
[1/1]:
- Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live
Li, Mang, He, Zhang, Mao, Chen, Zhou, Cheung, Gonzalez, Stoica
https://arxiv.org/abs/2511.02230 https://mastoxiv.page/@arXiv_csOS_bot/115496104707744234
toXiv_bot_toot

Simulation and optimization of the Active Magnetic Shield of the n2EDM experiment
N. J. Ayres, G. Ban, G. Bison, K. Bodek, V. Bondar, T. Bouillaud, G. L. Caratsch, E. Chanel, W. Chen, C. Crawford, V. Czamler, C. B. Doorenbos, S. Emmeneger, S. K. Ermakov, M. Ferry, M. Fertl, A. Fratangelo, D. Galbinski, W. C. Griffith, Z. D. Grujic, K. Kirch, V. Kletzl, J. Krempel, B. Lauss, T. Lefort, A. Lejuez, K. Michielsen, J. Micko, P. Mullan, O. Naviliat-Cuncic, F. M. Piegsa, G. Pignol, C. Pistillo, I. Rien\"acker, D. Ries, S. Roccia, D. Rozp\k{e}dzik, L. Sanchez-Real Zielniewicz, N. von Schickh, P. Schmidt-Wellenburg, E. P. Segarra, L. Segner, N. Severijns, K. Svirina, J. Thorne, J. Vankeirsbilck, N. Yazdandoost, J. Zejma, N. Ziehl, G. Zsigmond
https://arxiv.org/abs/2601.22960 https://arxiv.org/pdf/2601.22960 https://arxiv.org/html/2601.22960
arXiv:2601.22960v1 Announce Type: new
Abstract: The n2EDM experiment at the Paul Scherrer Institute aims to conduct a high-sensitivity search for the electric dipole moment of the neutron. Magnetic stability and control are achieved through a combination of passive shielding, provided by a magnetically shielded room (MSR), and a surrounding active field compensation system by an Active Magnetic Shield (AMS). The AMS is a feedback-controlled system of eight coils spanned on an irregular grid, designed to provide magnetic stability to the enclosed volume by actively suppressing external magnetic disturbances. It can compensate static and variable magnetic fields up to $\pm 50$ $\mu$T (homogeneous components) and $\pm 5$ $\mu$T/m (first-order gradients), suppressing them to a few $\mu$T in the sub-Hertz frequency range. We present a full finite element simulation of magnetic fields generated by the AMS in the presence of the MSR. This simulation is of sufficient accuracy to approach our measurements. We demonstrate how the simulation can be used with an example, obtaining an optimal number and placement of feedback sensors using genetic algorithms.
toXiv_bot_toot

Identifying Mechanism of Energy-Resolved Attoclock
Jia'nan Wu, Shiqi Shen, Jiayin Che, Shang Wang, Weiyan Li, Guoguo Xin, Yanjun Chen
https://arxiv.org/abs/2601.05830 https:…

Replaced article(s) found for cond-mat.str-el. https://arxiv.org/list/cond-mat.str-el/new
[2/2]:
- Non-Equilibrium Phase Transition in a Boundary-Driven Dissipative Fermionic Chain
Hao Chen, Wucheng Zhang, Manas Kulkarni, Abhinav Prem

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/6]:
- Performance Asymmetry in Model-Based Reinforcement Learning
Jing Yu Lim, Rushi Shah, Zarif Ikram, Samson Yu, Haozhe Ma, Tze-Yun Leong, Dianbo Liu
https://arxiv.org/abs/2505.19698 https://mastoxiv.page/@arXiv_csLG_bot/114578810521008766
- Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependenc...
Jinkwan Jang, Hyungjin Park, Jinmyeong Choi, Taesup Kim
https://arxiv.org/abs/2506.08660 https://mastoxiv.page/@arXiv_csLG_bot/114664238967892509
- Wasserstein Barycenter Soft Actor-Critic
Zahra Shahrooei, Ali Baheri
https://arxiv.org/abs/2506.10167 https://mastoxiv.page/@arXiv_csLG_bot/114675175949432731
- Foundation Models for Causal Inference via Prior-Data Fitted Networks
Yuchen Ma, Dennis Frauen, Emil Javurek, Stefan Feuerriegel
https://arxiv.org/abs/2506.10914 https://mastoxiv.page/@arXiv_csLG_bot/114675529854402158
- FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
https://arxiv.org/abs/2506.18481 https://mastoxiv.page/@arXiv_csLG_bot/114738421450807709
- Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev, Edvard Khalafyan, Alexey Zaytsev
https://arxiv.org/abs/2506.21220 https://mastoxiv.page/@arXiv_csLG_bot/114754764750730849
- Transfer Learning in Infinite Width Feature Learning Networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
https://arxiv.org/abs/2507.04448 https://mastoxiv.page/@arXiv_csLG_bot/114818005803079705
- A hierarchy tree data structure for behavior-based user segment representation
Liu, Kang, Iyer, Malik, Li, Wang, Lu, Zhao, Wang, Liu, Liu, Liang, Yu
https://arxiv.org/abs/2508.01115 https://mastoxiv.page/@arXiv_csLG_bot/114975999992144374
- One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Lea...
Thanh Nguyen, Chang D. Yoo
https://arxiv.org/abs/2508.13904 https://mastoxiv.page/@arXiv_csLG_bot/115060568241390847
- Uncertainty Propagation Networks for Neural Ordinary Differential Equations
Hadi Jahanshahi, Zheng H. Zhu
https://arxiv.org/abs/2508.16815 https://mastoxiv.page/@arXiv_csLG_bot/115094785677272005
- Learning Unified Representations from Heterogeneous Data for Robust Heart Rate Modeling
Zhengdong Huang, Zicheng Xie, Wentao Tian, Jingyu Liu, Lunhong Dong, Peng Yang
https://arxiv.org/abs/2508.21785 https://mastoxiv.page/@arXiv_csLG_bot/115128450608548173
- Monte Carlo Tree Diffusion with Multiple Experts for Protein Design
Liu, Cao, Jiang, Luo, Duan, Wang, Sosnick, Xu, Stevens
https://arxiv.org/abs/2509.15796 https://mastoxiv.page/@arXiv_csLG_bot/115247429156900905
- From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting
Xilin Dai, Zhijian Xu, Wanxu Cai, Qiang Xu
https://arxiv.org/abs/2509.19975 https://mastoxiv.page/@arXiv_csLG_bot/115264498084813952
- Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
https://arxiv.org/abs/2509.21895 https://mastoxiv.page/@arXiv_csLG_bot/115287261047939306
- From Parameters to Behaviors: Unsupervised Compression of the Policy Space
Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
https://arxiv.org/abs/2509.22566 https://mastoxiv.page/@arXiv_csLG_bot/115287379672141023
- RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
Haoyu He, Haozheng Luo, Yan Chen, Qi R. Wang
https://arxiv.org/abs/2509.23115 https://mastoxiv.page/@arXiv_csLG_bot/115293273559547106
- Polychromic Objectives for Reinforcement Learning
Jubayer Ibn Hamid, Ifdita Hasan Orney, Ellen Xu, Chelsea Finn, Dorsa Sadigh
https://arxiv.org/abs/2509.25424 https://mastoxiv.page/@arXiv_csLG_bot/115298579764580635
- Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Siddarth Venkatraman, et al.
https://arxiv.org/abs/2509.26626 https://mastoxiv.page/@arXiv_csLG_bot/115298789487177431
- Cautious Weight Decay
Chen, Li, Liang, Su, Xie, Pierse, Liang, Lao, Liu
https://arxiv.org/abs/2510.12402 https://mastoxiv.page/@arXiv_csLG_bot/115377759317818093
- TeamFormer: Shallow Parallel Transformers with Progressive Approximation
Wei Wang, Xiao-Yong Wei, Qing Li
https://arxiv.org/abs/2510.15425 https://mastoxiv.page/@arXiv_csLG_bot/115405933861293858
- Latent-Augmented Discrete Diffusion Models
Dario Shariatian, Alain Durmus, Umut Simsekli, Stefano Peluchetti
https://arxiv.org/abs/2510.18114 https://mastoxiv.page/@arXiv_csLG_bot/115417332500265972
- Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Method...
Mary E. An, Paul Griffin, Jonathan G. Stine, Ramakrishna Balakrishnan, Soundar Kumara
https://arxiv.org/abs/2510.22293 https://mastoxiv.page/@arXiv_csLG_bot/115451746201804373
toXiv_bot_toot

JUST-DUB-IT: Video Dubbing via Joint Audio-Visual Diffusion
Anthony Chen, Naomi Ken Korem, Tavi Halperin, Matan Ben Yosef, Urska Jelercic, Ofir Bibi, Or Patashnik, Daniel Cohen-Or
https://arxiv.org/abs/2601.22143 https://arxiv.org/pdf/2601.22143 https://arxiv.org/html/2601.22143
arXiv:2601.22143v1 Announce Type: new
Abstract: Audio-Visual Foundation Models, which are pretrained to jointly generate sound and visual content, have recently shown an unprecedented ability to model multi-modal generation and editing, opening new opportunities for downstream tasks. Among these tasks, video dubbing could greatly benefit from such priors, yet most existing solutions still rely on complex, task-specific pipelines that struggle in real-world settings. In this work, we introduce a single-model approach that adapts a foundational audio-video diffusion model for video-to-video dubbing via a lightweight LoRA. The LoRA enables the model to condition on an input audio-video while jointly generating translated audio and synchronized facial motion. To train this LoRA, we leverage the generative model itself to synthesize paired multilingual videos of the same speaker. Specifically, we generate multilingual videos with language switches within a single clip, and then inpaint the face and audio in each half to match the language of the other half. By leveraging the rich generative prior of the audio-visual model, our approach preserves speaker identity and lip synchronization while remaining robust to complex motion and real-world dynamics. We demonstrate that our approach produces high-quality dubbed videos with improved visual fidelity, lip synchronization, and robustness compared to existing dubbing pipelines.
toXiv_bot_toot

Atomic data benchmarked by Large-scale Multiconfiguration Dirac-Hartree-Fock Calculations for Beryllium
Sijie Wu, Shaowei Tian, Ran Si, Kai Wang, Per J\"onsson, Gediminas Gaigalas, Michel Godefroid, Anish Mayur Amarsi, Chongyang Chen
https://arxiv.org/abs/2603.11098

Mesh Splatting for End-to-end Multiview Surface Reconstruction
Ruiqi Zhang, Jiacheng Wu, Jie Chen
https://arxiv.org/abs/2601.21400 https://arxiv.org/pdf/2601.21400 https://arxiv.org/html/2601.21400
arXiv:2601.21400v1 Announce Type: new
Abstract: Surfaces are typically represented as meshes, which can be extracted from volumetric fields via meshing or optimized directly as surface parameterizations. Volumetric representations occupy 3D space and have a large effective receptive field along rays, enabling stable and efficient optimization via volumetric rendering; however, subsequent meshing often produces overly dense meshes and introduces accumulated errors. In contrast, pure surface methods avoid meshing but capture only boundary geometry with a single-layer receptive field, making it difficult to learn intricate geometric details and increasing reliance on priors (e.g., shading or normals). We bridge this gap by differentiably turning a surface representation into a volumetric one, enabling end-to-end surface reconstruction via volumetric rendering to model complex geometries. Specifically, we soften a mesh into multiple semi-transparent layers that remain differentiable with respect to the base mesh, endowing it with a controllable 3D receptive field. Combined with a splatting-based renderer and a topology-control strategy, our method can be optimized in about 20 minutes to achieve accurate surface reconstruction while substantially improving mesh quality.
toXiv_bot_toot

Strong Electron Correlation Identified in Planetary Atomic Structure
Xinglong Yu, Yongyan Han, Zhenjie Shen, Yong-Kang Fang, Shushu Ruan, Jie Liu, Zhixian Wu, Xincheng Wang, Ahai Chen, Wei-Chao Jiang, Kiyoshi Ueda, Liang-You Peng, Yuhai Jiang
https://arxiv.org/abs/2603.09102

ProxyFL: A Proxy-Guided Framework for Federated Semi-Supervised Learning
Duowen Chen, Yan Wang
https://arxiv.org/abs/2602.21078 https://arxiv.org/pdf/2602.21078 https://arxiv.org/html/2602.21078
arXiv:2602.21078v1 Announce Type: new
Abstract: Federated Semi-Supervised Learning (FSSL) aims to collaboratively train a global model across clients by leveraging partially-annotated local data in a privacy-preserving manner. In FSSL, data heterogeneity is a challenging issue, which exists both across clients and within clients. External heterogeneity refers to the data distribution discrepancy across different clients, while internal heterogeneity represents the mismatch between labeled and unlabeled data within clients. Most FSSL methods typically design fixed or dynamic parameter aggregation strategies to collect client knowledge on the server (external) and / or filter out low-confidence unlabeled samples to reduce mistakes in local client (internal). But, the former is hard to precisely fit the ideal global distribution via direct weights, and the latter results in fewer data participation into FL training. To this end, we propose a proxy-guided framework called ProxyFL that focuses on simultaneously mitigating external and internal heterogeneity via a unified proxy. I.e., we consider the learnable weights of classifier as proxy to simulate the category distribution both locally and globally. For external, we explicitly optimize global proxy against outliers instead of direct weights; for internal, we re-include the discarded samples into training by a positive-negative proxy pool to mitigate the impact of potentially-incorrect pseudo-labels. Insight experiments & theoretical analysis show our significant performance and convergence in FSSL.
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New energy conversion system based on charge-exchange and inner-shell electron transitions
Tianrui Li, Yi Jiang, Chen Zhao, Bingsheng Tu, Peining Chen, Jiajun Qin, Huisheng Peng
https://arxiv.org/abs/2601.17015

Regret-Guided Search Control for Efficient Learning in AlphaZero
Yun-Jui Tsai, Wei-Yu Chen, Yan-Ru Ju, Yu-Hung Chang, Ti-Rong Wu
https://arxiv.org/abs/2602.20809 https://arxiv.org/pdf/2602.20809 https://arxiv.org/html/2602.20809
arXiv:2602.20809v1 Announce Type: new
Abstract: Reinforcement learning (RL) agents achieve remarkable performance but remain far less learning-efficient than humans. While RL agents require extensive self-play games to extract useful signals, humans often need only a few games, improving rapidly by repeatedly revisiting states where mistakes occurred. This idea, known as search control, aims to restart from valuable states rather than always from the initial state. In AlphaZero, prior work Go-Exploit applies this idea by sampling past states from self-play or search trees, but it treats all states equally, regardless of their learning potential. We propose Regret-Guided Search Control (RGSC), which extends AlphaZero with a regret network that learns to identify high-regret states, where the agent's evaluation diverges most from the actual outcome. These states are collected from both self-play trajectories and MCTS nodes, stored in a prioritized regret buffer, and reused as new starting positions. Across 9x9 Go, 10x10 Othello, and 11x11 Hex, RGSC outperforms AlphaZero and Go-Exploit by an average of 77 and 89 Elo, respectively. When training on a well-trained 9x9 Go model, RGSC further improves the win rate against KataGo from 69.3% to 78.2%, while both baselines show no improvement. These results demonstrate that RGSC provides an effective mechanism for search control, improving both efficiency and robustness of AlphaZero training. Our code is available at https://rlg.iis.sinica.edu.tw/papers/rgsc.
toXiv_bot_toot

Crosslisted article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Optimization and Mobile Deployment for Anthropocene Neural Style Transfer
Po-Hsun Chen, Ivan C. H. Liu
https://arxiv.org/abs/2601.21141 https://mastoxiv.page/@arXiv_csHC_bot/115983012560898066
- HiFi-Mesh: High-Fidelity Efficient 3D Mesh Generation via Compact Autoregressive Dependence
Yanfeng Li, Tao Tan, Qingquan Gao, Zhiwen Cao, Xiaohong liu, Yue Sun
https://arxiv.org/abs/2601.21314 https://mastoxiv.page/@arXiv_csCV_bot/115983484680840673
- Synthetic-to-Real Domain Bridging for Single-View 3D Reconstruction of Ships for Maritime Monitoring
Borja Carrillo-Perez, Felix Sattler, Angel Bueno Rodriguez, Maurice Stephan, Sarah Barnes
https://arxiv.org/abs/2601.21786 https://mastoxiv.page/@arXiv_csCV_bot/115983653113440181
- EditYourself: Audio-Driven Generation and Manipulation of Talking Head Videos with Diffusion Tran...
Flynn, Paier, Dinev, Nguyen, Poghosyan, Toribio, Banerjee, Gafni
https://arxiv.org/abs/2601.22127 https://mastoxiv.page/@arXiv_csCV_bot/115983720617201966
toXiv_bot_toot

Crosslisted article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Exo-Plore: Exploring Exoskeleton Control Space through Human-aligned Simulation
Geonho Leem, Jaedong Lee, Jehee Lee, Seungmoon Song, Jungdam Won
https://arxiv.org/abs/2601.22550 https://mastoxiv.page/@arXiv_csRO_bot/116000313826549982
- Synthetic Abundance Maps for Unsupervised Super-Resolution of Hyperspectral Remote Sensing Images
Xinxin Xu, Yann Gousseau, Christophe Kervazo, Sa\"id Ladjal
https://arxiv.org/abs/2601.22755 https://mastoxiv.page/@arXiv_eessIV_bot/116000368902815664
- Under-Canopy Terrain Reconstruction in Dense Forests Using RGB Imaging and Neural 3D Reconstruction
Refael Sheffer, Chen Pinchover, Haim Zisman, Dror Ozeri, Roee Litman
https://arxiv.org/abs/2601.22861 https://mastoxiv.page/@arXiv_csCV_bot/116000605470776021
toXiv_bot_toot

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- AI-Accelerated Qubit Readout at the Single-Photon Level for Scalable Atomic Quantum Processors
Zhou, Wang, Tian, Huang, Chen, Li, Xu, Chen, Shen

LoD-Structured 3D Gaussian Splatting for Streaming Video Reconstruction
Xinhui Liu, Can Wang, Lei Liu, Zhenghao Chen, Wei Jiang, Wei Wang, Dong Xu
https://arxiv.org/abs/2601.18475 https://arxiv.org/pdf/2601.18475 https://arxiv.org/html/2601.18475
arXiv:2601.18475v1 Announce Type: new
Abstract: Free-Viewpoint Video (FVV) reconstruction enables photorealistic and interactive 3D scene visualization; however, real-time streaming is often bottlenecked by sparse-view inputs, prohibitive training costs, and bandwidth constraints. While recent 3D Gaussian Splatting (3DGS) has advanced FVV due to its superior rendering speed, Streaming Free-Viewpoint Video (SFVV) introduces additional demands for rapid optimization, high-fidelity reconstruction under sparse constraints, and minimal storage footprints. To bridge this gap, we propose StreamLoD-GS, an LoD-based Gaussian Splatting framework designed specifically for SFVV. Our approach integrates three core innovations: 1) an Anchor- and Octree-based LoD-structured 3DGS with a hierarchical Gaussian dropout technique to ensure efficient and stable optimization while maintaining high-quality rendering; 2) a GMM-based motion partitioning mechanism that separates dynamic and static content, refining dynamic regions while preserving background stability; and 3) a quantized residual refinement framework that significantly reduces storage requirements without compromising visual fidelity. Extensive experiments demonstrate that StreamLoD-GS achieves competitive or state-of-the-art performance in terms of quality, efficiency, and storage.
toXiv_bot_toot

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- CASteer: Cross-Attention Steering for Controllable Concept Erasure
Gaintseva, Oncescu, Ma, Liu, Benning, Slabaugh, Deng, Elezi
https://arxiv.org/abs/2503.09630 https://mastoxiv.page/@arXiv_csGR_bot/114159563689274183
- Emergent morphogenesis via planar fabrication enabled by a reduced model of composites
Yupeng Zhang, Adam Alon, M. Khalid Jawed
https://arxiv.org/abs/2508.08198 https://mastoxiv.page/@arXiv_csGR_bot/115015041244278094
- DiffusionLight-Turbo: Accelerated Light Probes for Free via Single-Pass Chrome Ball Inpainting
Chinchuthakun, Phongthawee, Raj, Jampani, Khungurn, Suwajanakorn
https://arxiv.org/abs/2507.01305 https://mastoxiv.page/@arXiv_csCV_bot/114788643017213587
- Beyond Inpainting: Unleash 3D Understanding for Precise Camera-Controlled Video Generation
Dong-Yu Chen, Yixin Guo, Shuojin Yang, Tai-Jiang Mu, Shi-Min Hu
https://arxiv.org/abs/2601.10214 https://mastoxiv.page/@arXiv_csCV_bot/115904260738523976
toXiv_bot_toot

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[3/3]:
- Functional Continuous Decomposition
Teymur Aghayev
https://arxiv.org/abs/2602.20857 https://mastoxiv.page/@arXiv_eessSP_bot/116130499236089653
- SpatiaLQA: A Benchmark for Evaluating Spatial Logical Reasoning in Vision-Language Models
Xie, Zhang, Shan, Zhu, Tang, Wei, Song, Wan, Song
https://arxiv.org/abs/2602.20901 https://mastoxiv.page/@arXiv_csCV_bot/116130845273808954
- Some Simple Economics of AGI
Christian Catalini, Xiang Hui, Jane Wu
https://arxiv.org/abs/2602.20946 https://mastoxiv.page/@arXiv_econGN_bot/116130470423837005
- Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures
Yubin Ge, Yongsong Huang, Xiaofeng Liu
https://arxiv.org/abs/2602.20994 https://mastoxiv.page/@arXiv_eessIV_bot/116130212832138624
- MIP Candy: A Modular PyTorch Framework for Medical Image Processing
Tianhao Fu, Yucheng Chen
https://arxiv.org/abs/2602.21033 https://mastoxiv.page/@arXiv_csCV_bot/116130864279556063
- Empirically Calibrated Conditional Independence Tests
Milleno Pan, Antoine de Mathelin, Wesley Tansey
https://arxiv.org/abs/2602.21036 https://mastoxiv.page/@arXiv_statME_bot/116130690605113562
- Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise
Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet
https://arxiv.org/abs/2602.21039 https://mastoxiv.page/@arXiv_statML_bot/116130572661848449
- Position-Aware Sequential Attention for Accurate Next Item Recommendations
Timur Nabiev, Evgeny Frolov
https://arxiv.org/abs/2602.21052 https://mastoxiv.page/@arXiv_csIR_bot/116130263323086316
- Motivation is Something You Need
Mehdi Acheli, Walid Gaaloul
https://arxiv.org/abs/2602.21064 https://mastoxiv.page/@arXiv_csAI_bot/116130680774678580
- An Enhanced Projection Pursuit Tree Classifier with Visual Methods for Assessing Algorithmic Impr...
Natalia da Silva, Dianne Cook, Eun-Kyung Lee
https://arxiv.org/abs/2602.21130 https://mastoxiv.page/@arXiv_statML_bot/116130610674573081
- Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
Kimon Fountoulakis, David Mart\'inez-Rubio
https://arxiv.org/abs/2602.21138 https://mastoxiv.page/@arXiv_mathOC_bot/116130547076073836
- LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Jiang, Yang, Nath, Parida, Kulkarni, Xu, Xu, Anwar, Roth, Linguraru
https://arxiv.org/abs/2602.21142 https://mastoxiv.page/@arXiv_csCV_bot/116130871488694585
- A Benchmark for Deep Information Synthesis
Debjit Paul, et al.
https://arxiv.org/abs/2602.21143 https://mastoxiv.page/@arXiv_csAI_bot/116130692571594706
- Scaling State-Space Models on Multiple GPUs with Tensor Parallelism
Anurag Dutt, Nimit Shah, Hazem Masarani, Anshul Gandhi
https://arxiv.org/abs/2602.21144 https://mastoxiv.page/@arXiv_csDC_bot/116130520888343997
- Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions
Mame Diarra Toure, David A. Stephens
https://arxiv.org/abs/2602.21160 https://mastoxiv.page/@arXiv_statML_bot/116130618512594211
- Aletheia tackles FirstProof autonomously
Tony Feng, et al.
https://arxiv.org/abs/2602.21201 https://mastoxiv.page/@arXiv_csAI_bot/116130705679345625
- Squint: Fast Visual Reinforcement Learning for Sim-to-Real Robotics
Abdulaziz Almuzairee, Henrik I. Christensen
https://arxiv.org/abs/2602.21203 https://mastoxiv.page/@arXiv_csRO_bot/116130765974498223
toXiv_bot_toot

Characterization of Feshbach resonances in $^6\mathrm{Li}{-}^7\mathrm{Li}$ using improved interaction potentials
Jing-Chen Zhang, Paul Julienne, Yu Liu
https://arxiv.org/abs/2603.02361

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/6]:
- Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
Apurv Verma, NhatHai Phan, Shubhendu Trivedi
https://arxiv.org/abs/2506.04462 https://mastoxiv.page/@arXiv_csCL_bot/114635190037336859
- Sensory-Motor Control with Large Language Models via Iterative Policy Refinement
J\^onata Tyska Carvalho, Stefano Nolfi
https://arxiv.org/abs/2506.04867 https://mastoxiv.page/@arXiv_csAI_bot/114635187854195641
- ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution
de Carvalho, Popov, Kaatee, Correia, Th\'orisson, Li, Bj\"ornsson, Sigur{\dh}arson, Dibangoye
https://arxiv.org/abs/2506.13792 https://mastoxiv.page/@arXiv_csAI_bot/114703312162525342
- Feedback-driven recurrent quantum neural network universality
Lukas Gonon, Rodrigo Mart\'inez-Pe\~na, Juan-Pablo Ortega
https://arxiv.org/abs/2506.16332 https://mastoxiv.page/@arXiv_quantph_bot/114732532383196043
- Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
Cook, Sapora, Ahmadian, Khan, Rocktaschel, Foerster, Ruis
https://arxiv.org/abs/2506.18777 https://mastoxiv.page/@arXiv_csAI_bot/114738213040759661
- Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning
Jiechen Chen, Bipin Rajendran, Osvaldo Simeone
https://arxiv.org/abs/2506.21324 https://mastoxiv.page/@arXiv_csNE_bot/114754367612728319
- Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
Pierre Boudart (SIERRA), Pierre Gaillard (Thoth), Alessandro Rudi (PSL, DI-ENS, Inria)
https://arxiv.org/abs/2507.05306 https://mastoxiv.page/@arXiv_statML_bot/114822374525501660
- Characterizing State Space Model and Hybrid Language Model Performance with Long Context
Saptarshi Mitra, Rachid Karami, Haocheng Xu, Sitao Huang, Hyoukjun Kwon
https://arxiv.org/abs/2507.12442 https://mastoxiv.page/@arXiv_csAR_bot/114867589638074984
- Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Da...
Ayush Roy, Samin Enam, Jun Xia, Won Hwa Kim, Vishnu Suresh Lokhande
https://arxiv.org/abs/2507.19575 https://mastoxiv.page/@arXiv_csCV_bot/114935399825741861
- TASER: Table Agents for Schema-guided Extraction and Recommendation
Nicole Cho, Kirsty Fielding, William Watson, Sumitra Ganesh, Manuela Veloso
https://arxiv.org/abs/2508.13404 https://mastoxiv.page/@arXiv_csAI_bot/115060386723032051
- Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
Nuno Costa, Julija Zavadlav
https://arxiv.org/abs/2509.02060 https://mastoxiv.page/@arXiv_qbioBM_bot/115139546511384706
- PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models
Jeongjae Lee, Jong Chul Ye
https://arxiv.org/abs/2509.25774 https://mastoxiv.page/@arXiv_csCV_bot/115298580419859537
- Multi-hop Deep Joint Source-Channel Coding with Deep Hash Distillation for Semantically Aligned I...
Didrik Bergstr\"om, Deniz G\"und\"uz, Onur G\"unl\"u
https://arxiv.org/abs/2510.06868 https://mastoxiv.page/@arXiv_csIT_bot/115343320768797486
- MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile...
Chengshu Li, et al.
https://arxiv.org/abs/2510.18316 https://mastoxiv.page/@arXiv_csRO_bot/115416889485910123
- A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz
https://arxiv.org/abs/2510.20954 https://mastoxiv.page/@arXiv_statML_bot/115445273121677005
- Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
Bazinska, Mathys, Casucci, Rojas-Carulla, Davies, Souly, Pfister
https://arxiv.org/abs/2510.22620 https://mastoxiv.page/@arXiv_csCR_bot/115451397563132982
- Uncertainty Calibration of Multi-Label Bird Sound Classifiers
Raphael Schwinger, Ben McEwen, Vincent S. Kather, Ren\'e Heinrich, Lukas Rauch, Sven Tomforde
https://arxiv.org/abs/2511.08261 https://mastoxiv.page/@arXiv_csSD_bot/115535982708483824
- Two-dimensional RMSD projections for reaction path visualization and validation
Rohit Goswami (Institute IMX and Lab-COSMO, \'Ecole polytechnique f\'ed\'erale de Lausanne)
https://arxiv.org/abs/2512.07329 https://mastoxiv.page/@arXiv_physicschemph_bot/115688910885717951
- Distribution-informed Online Conformal Prediction
Dongjian Hu, Junxi Wu, Shu-Tao Xia, Changliang Zou
https://arxiv.org/abs/2512.07770 https://mastoxiv.page/@arXiv_statML_bot/115689281155541568
- Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss
Ang Lv, Jin Ma, Yiyuan Ma, Siyuan Qiao
https://arxiv.org/abs/2512.23447 https://mastoxiv.page/@arXiv_csCL_bot/115808311310246601
toXiv_bot_toot

Probing a Fifth Force in Muonic Atoms through Lamb Shifts and Hyperfine Structure
Xiaoxuan Lin, Qian Wu, Wei Kou, Xurong Chen
https://arxiv.org/abs/2603.01429 https://

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/3]:
- SMaRT: Online Reusable Resource Assignment and an Application to Mediation in the Kenyan Judiciary
Farabi, Pinto, Lu, Ramos-Maqueda, Das, Deeb, Sautmann
https://arxiv.org/abs/2602.18431 https://mastoxiv.page/@arXiv_csCY_bot/116119352329590193
- Benchmarking Distilled Language Models: Performance and Efficiency in Resource-Constrained Settings
Sachin Gopal Wani, Eric Page, Ajay Dholakia, David Ellison
https://arxiv.org/abs/2602.20164 https://mastoxiv.page/@arXiv_csCL_bot/116130101399805837
- VISION-ICE: Video-based Interpretation and Spatial Identification of Arrhythmia Origins via Neura...
Dorsa EPMoghaddam, Feng Gao, Drew Bernard, Kavya Sinha, Mehdi Razavi, Behnaam Aazhang
https://arxiv.org/abs/2602.20165 https://mastoxiv.page/@arXiv_csCV_bot/116130222034322594
- Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Un...
KMA Solaiman, Joshua Sebastian, Karma Tobden
https://arxiv.org/abs/2602.20168 https://mastoxiv.page/@arXiv_csCY_bot/116130239074411770
- Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Yang, Tian, Jia, Zhang, Zheng, Wang, Su, He, Liu, Lan
https://arxiv.org/abs/2602.20176 https://mastoxiv.page/@arXiv_qbioBM_bot/116130281674122586
- Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic St...
Aniruddha Bora, Isabel K. Alvarez, Julie Chalfant, Chryssostomos Chryssostomidis
https://arxiv.org/abs/2602.20177 https://mastoxiv.page/@arXiv_csNE_bot/116130397676559696
- Data-Driven Deep MIMO Detection:Network Architectures and Generalization Analysis
Yongwei Yi, Xinping Yi, Wenjin Wang, Xiao Li, Shi Jin
https://arxiv.org/abs/2602.20178 https://mastoxiv.page/@arXiv_eessSP_bot/116130257424413457
- OrgFlow: Generative Modeling of Organic Crystal Structures from Molecular Graphs
Mohammadmahdi Vahediahmar, Matthew A. McDonald, Feng Liu
https://arxiv.org/abs/2602.20195 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/116130271189617558
- KEMP-PIP: A Feature-Fusion Based Approach for Pro-inflammatory Peptide Prediction
Soumik Deb Niloy, Md. Fahmid-Ul-Alam Juboraj, Swakkhar Shatabda
https://arxiv.org/abs/2602.20198 https://mastoxiv.page/@arXiv_qbioQM_bot/116130341315320687
- Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
Shaorong Chen, Jingbo Zhou, Jun Xia
https://arxiv.org/abs/2602.20209 https://mastoxiv.page/@arXiv_qbioQM_bot/116130374083646541
- The Sim-to-Real Gap in MRS Quantification: A Systematic Deep Learning Validation for GABA
Zien Ma, S. M. Shermer, Oktay Karaku\c{s}, Frank C. Langbein
https://arxiv.org/abs/2602.20289 https://mastoxiv.page/@arXiv_eessSP_bot/116130267228834775
- Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Appro...
Haochen Zhang, Zhong Zheng, Lingzhou Xue
https://arxiv.org/abs/2602.20297 https://mastoxiv.page/@arXiv_statML_bot/116130255458256497
- Multilevel Determinants of Overweight and Obesity Among U.S. Children Aged 10-17: Comparative Eva...
Joyanta Jyoti Mondal
https://arxiv.org/abs/2602.20303 https://mastoxiv.page/@arXiv_csAI_bot/116130097466859145
- An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes ...
Shyr, Hu, Tinker, Cassini, Byram, Hamid, Fabbri, Wright, Peterson, Bastarache, Xu
https://arxiv.org/abs/2602.20324 https://mastoxiv.page/@arXiv_csAI_bot/116130100089848459
- Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Th...
Jingcheng Yang, Tianhu Xiong, Shengyi Qian, Klara Nahrstedt, Mingyuan Wu
https://arxiv.org/abs/2602.20330 https://mastoxiv.page/@arXiv_csCV_bot/116130463214879334
- No One Size Fits All: QueryBandits for Hallucination Mitigation
Nicole Cho, William Watson, Alec Koppel, Sumitra Ganesh, Manuela Veloso
https://arxiv.org/abs/2602.20332 https://mastoxiv.page/@arXiv_csCL_bot/116130370809116915
- Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Mohanad Obeed, Ming Jian
https://arxiv.org/abs/2602.20361 https://mastoxiv.page/@arXiv_csIT_bot/116130289537785136
- Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
Joel Persson, Jurri\"en Bakker, Dennis Bohle, Stefan Feuerriegel, Florian von Wangenheim
https://arxiv.org/abs/2602.20383 https://mastoxiv.page/@arXiv_statME_bot/116130509065601748
- Selecting Optimal Variable Order in Autoregressive Ising Models
Shiba Biswal, Marc Vuffray, Andrey Y. Lokhov
https://arxiv.org/abs/2602.20394 https://mastoxiv.page/@arXiv_statML_bot/116130299369541741
toXiv_bot_toot

Time-domain measurement of Auger electron dynamics in xenon atoms after giant resonant photoionization
Mahmudul Hasan, Jingsong Gao, Hao Liang, Yiming Yuan, Zach Eisenhutt, Ming-Shian Tsai, Ming-Chang Chen, Hans Jakob W\"orner, Artem Rudenko, Meng Han
https://arxiv.org/abs/2512.19965