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@njamster@mastodon.gamedev.place
2026-02-08 08:29:47

If you can, go watch "It Was Just An Accident". It's good (albeit a little slow) and will stay with you long after the credits rolled. Can't say I've watched anything similar yet.
letterboxd.com/njamster/film/i

A ★★★★ review of It Was Just an Accident (2025)
Takes quite a while to get going and is pretty slow-paced in general, but if you can handle that, you're in for a treat! During the middle part Panahi masterfully manages the really impressive tightrope act of being almost comedic despite the very heavy topic. The central question of "Did he really do it?" remains open right until the end, and will keep you at the edge of your seat, despite the rather minimal (almost "chamber play"-like) set pieces and cast. And the ambiguous ending is just... …

@cdarwin@c.im
2026-01-30 21:14:56

Jack Kerouac’s original typescript scroll for "On the Road"
– the 37 metre (121 ft) long roll of paper on which he typed his defining Beat novel in a three-week burst
– will go under the hammer at Christie’s in March, with a sale estimate of £1.8m to £2.9m ($2.5m to $4m).
The scroll is one of the centrepieces of the Jim Irsay Collection,
one of the most extensive private collections of music, literary,
film and sports memorabilia ever assembled.
…

Jack Kerouac’s 37 metre-long, first draft scroll of On the Road to be auctioned
The draft – one of the Beat Generation’s defining artefacts – will be part of a wider sale of pieces from the Jim Irsay Collection at Christie’s in March

@pygospa@social.linux.pizza
2026-03-02 15:20:27

Yesterday was the "Digital Independence Day", which I only learned of, today. Coincidentally yesterday I wrote my first blog post in years! I used to be on wordpress.com for nearly a decade, then moved my blogging to #g #facebook,

hello, world!
Why I am back blogging, but switched from WordPress.com to Zola and how I hosted it on Codeberg Pages

@arXiv_physicsinsdet_bot@mastoxiv.page
2026-02-03 09:09:47

Gamma Imagers for Nuclear Security and Nuclear Forensics: Recommendations based on results from a side-by-side intercomparison
L. E. Sinclair, P. R. B. Saull, A. McCann, A. M. L. MacLeod, N. J. Murtha, A. El-Jaby, G. Jonkmans
arxiv.org/abs/2602.00826 arxiv.org/pdf/2602.00826 arxiv.org/html/2602.00826
arXiv:2602.00826v1 Announce Type: new
Abstract: Nuclear security operations and forensic investigations require the utilization of a suite of instruments ranging from passive gamma spectrometers to high-precision laboratory sample analyzers. Gamma spectroscopy survey is further broken down into wide-area search performed with large-volume scintillator-based mobile survey spectrometers which are integrated with geographic position sensors for mapping and identification of hot zones, and high-precision long-dwell measurements using solid state spectrometers for follow-on characterization to establish isotopic content and ratios. While performing well at detecting the presence, quantity and type of radioactivity, all of these methods have limited ability to determine the location of a source of radioactivity. In recent years, technology advances have resulted in gamma imager devices which can create an image of the distribution of radioactive sources using the gamma emissions which accompany radioactive decay, and overlay this on an optical photograph of the environment. These gamma imaging devices have arisen out of methods developed for medical physics, experimental particle physics, and astrophysics, resulting in a proliferation of different technological approaches. Those responsible for establishing a nuclear security concept of operations, require guidance to choose the proper gamma imager for each of the application spaces in a tiered response. Here the results of an intercomparison of two gamma imagers based on two widely different technologies, semiconductor and scintillator detectors, are presented. The optimal utilization of these imaging technologies in a tiered response is discussed based on the results of the trial. Finally, an outlook on future directions for gamma imaging advances is provided.
toXiv_bot_toot

@arXiv_csGR_bot@mastoxiv.page
2026-02-04 02:32:29

Replaced article(s) found for cs.GR. 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
arxiv.org/abs/2509.00406 mastoxiv.page/@arXiv_csGR_bot/
- F-scheduler: illuminating the free-lunch design space for fast sampling of diffusion models
Zilai Li, Lujia Bai
arxiv.org/abs/2510.02390 mastoxiv.page/@arXiv_csGR_bot/
- Mesh Splatting for End-to-end Multiview Surface Reconstruction
Ruiqi Zhang, Jiacheng Wu, Jie Chen
arxiv.org/abs/2601.21400 mastoxiv.page/@arXiv_csGR_bot/
- InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions
Sirui Xu, Hung Yu Ling, Yu-Xiong Wang, Liang-Yan Gui
arxiv.org/abs/2502.20390 mastoxiv.page/@arXiv_csCV_bot/
- Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerate...
Zhaowen Fan
arxiv.org/abs/2601.06135 mastoxiv.page/@arXiv_csLG_bot/
- Under-Canopy Terrain Reconstruction in Dense Forests Using RGB Imaging and Neural 3D Reconstruction
Refael Sheffer, Chen Pinchover, Haim Zisman, Dror Ozeri, Roee Litman
arxiv.org/abs/2601.22861 mastoxiv.page/@arXiv_csCV_bot/
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@arXiv_csLG_bot@mastoxiv.page
2026-02-25 12:33:22

Crosslisted article(s) found for cs.LG. 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
arxiv.org/abs/2602.18431 mastoxiv.page/@arXiv_csCY_bot/
- Benchmarking Distilled Language Models: Performance and Efficiency in Resource-Constrained Settings
Sachin Gopal Wani, Eric Page, Ajay Dholakia, David Ellison
arxiv.org/abs/2602.20164 mastoxiv.page/@arXiv_csCL_bot/
- 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
arxiv.org/abs/2602.20165 mastoxiv.page/@arXiv_csCV_bot/
- Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Un...
KMA Solaiman, Joshua Sebastian, Karma Tobden
arxiv.org/abs/2602.20168 mastoxiv.page/@arXiv_csCY_bot/
- Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design
Yang, Tian, Jia, Zhang, Zheng, Wang, Su, He, Liu, Lan
arxiv.org/abs/2602.20176 mastoxiv.page/@arXiv_qbioBM_bo
- Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic St...
Aniruddha Bora, Isabel K. Alvarez, Julie Chalfant, Chryssostomos Chryssostomidis
arxiv.org/abs/2602.20177 mastoxiv.page/@arXiv_csNE_bot/
- Data-Driven Deep MIMO Detection:Network Architectures and Generalization Analysis
Yongwei Yi, Xinping Yi, Wenjin Wang, Xiao Li, Shi Jin
arxiv.org/abs/2602.20178 mastoxiv.page/@arXiv_eessSP_bo
- OrgFlow: Generative Modeling of Organic Crystal Structures from Molecular Graphs
Mohammadmahdi Vahediahmar, Matthew A. McDonald, Feng Liu
arxiv.org/abs/2602.20195 mastoxiv.page/@arXiv_condmatmt
- KEMP-PIP: A Feature-Fusion Based Approach for Pro-inflammatory Peptide Prediction
Soumik Deb Niloy, Md. Fahmid-Ul-Alam Juboraj, Swakkhar Shatabda
arxiv.org/abs/2602.20198 mastoxiv.page/@arXiv_qbioQM_bo
- Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
Shaorong Chen, Jingbo Zhou, Jun Xia
arxiv.org/abs/2602.20209 mastoxiv.page/@arXiv_qbioQM_bo
- 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
arxiv.org/abs/2602.20289 mastoxiv.page/@arXiv_eessSP_bo
- Gap-Dependent Bounds for Nearly Minimax Optimal Reinforcement Learning with Linear Function Appro...
Haochen Zhang, Zhong Zheng, Lingzhou Xue
arxiv.org/abs/2602.20297 mastoxiv.page/@arXiv_statML_bo
- Multilevel Determinants of Overweight and Obesity Among U.S. Children Aged 10-17: Comparative Eva...
Joyanta Jyoti Mondal
arxiv.org/abs/2602.20303 mastoxiv.page/@arXiv_csAI_bot/
- 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
arxiv.org/abs/2602.20324 mastoxiv.page/@arXiv_csAI_bot/
- Circuit Tracing in Vision-Language Models: Understanding the Internal Mechanisms of Multimodal Th...
Jingcheng Yang, Tianhu Xiong, Shengyi Qian, Klara Nahrstedt, Mingyuan Wu
arxiv.org/abs/2602.20330 mastoxiv.page/@arXiv_csCV_bot/
- No One Size Fits All: QueryBandits for Hallucination Mitigation
Nicole Cho, William Watson, Alec Koppel, Sumitra Ganesh, Manuela Veloso
arxiv.org/abs/2602.20332 mastoxiv.page/@arXiv_csCL_bot/
- Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Mohanad Obeed, Ming Jian
arxiv.org/abs/2602.20361 mastoxiv.page/@arXiv_csIT_bot/
- Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
Joel Persson, Jurri\"en Bakker, Dennis Bohle, Stefan Feuerriegel, Florian von Wangenheim
arxiv.org/abs/2602.20383 mastoxiv.page/@arXiv_statME_bo
- Selecting Optimal Variable Order in Autoregressive Ising Models
Shiba Biswal, Marc Vuffray, Andrey Y. Lokhov
arxiv.org/abs/2602.20394 mastoxiv.page/@arXiv_statML_bo
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@arXiv_csCL_bot@mastoxiv.page
2026-03-31 11:13:03

Replaced article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[4/5]:
- Retrieving Climate Change Disinformation by Narrative
Upravitelev, Solopova, Jakob, Sahitaj, M\"oller, Schmitt
arxiv.org/abs/2603.22015 mastoxiv.page/@arXiv_csCL_bot/
- PaperVoyager : Building Interactive Web with Visual Language Models
Dasen Dai, Biao Wu, Meng Fang, Wenhao Wang
arxiv.org/abs/2603.22999 mastoxiv.page/@arXiv_csCL_bot/
- Continual Robot Skill and Task Learning via Dialogue
Weiwei Gu, Suresh Kondepudi, Anmol Gupta, Lixiao Huang, Nakul Gopalan
arxiv.org/abs/2409.03166 mastoxiv.page/@arXiv_csRO_bot/
- Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke
arxiv.org/abs/2503.05371 mastoxiv.page/@arXiv_csLG_bot/
- SkillFlow: Scalable and Efficient Agent Skill Retrieval System
Fangzhou Li, Pagkratios Tagkopoulos, Ilias Tagkopoulos
arxiv.org/abs/2504.06188 mastoxiv.page/@arXiv_csAI_bot/
- Large Language Models for Computer-Aided Design: A Survey
Licheng Zhang, Bach Le, Naveed Akhtar, Siew-Kei Lam, Tuan Ngo
arxiv.org/abs/2505.08137 mastoxiv.page/@arXiv_csLG_bot/
- Structured Agent Distillation for Large Language Model
Liu, Kong, Dong, Yang, Li, Tang, Yuan, Niu, Zhang, Zhao, Lin, Huang, Wang
arxiv.org/abs/2505.13820 mastoxiv.page/@arXiv_csLG_bot/
- VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction
Fan, Zhang, Li, Zhang, Chen, Hu, Wang, Qu, Zhou, Wang, Yan, Xu, Theiss, Chen, Li, Tu, Wang, Ranjan
arxiv.org/abs/2505.20279 mastoxiv.page/@arXiv_csCV_bot/
- Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Bhattacharjee, Tian, Rubin, Lo, Merchant, Hanson, Gounley, Tandon
arxiv.org/abs/2506.04450 mastoxiv.page/@arXiv_csCR_bot/
- L-MARS: Legal Multi-Agent Workflow with Orchestrated Reasoning and Agentic Search
Ziqi Wang, Boqin Yuan
arxiv.org/abs/2509.00761 mastoxiv.page/@arXiv_csAI_bot/
- Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking
Han, Huang, Liao, Jiang, Lu, Zhao, Wang, Zhou, Jiang, Liang, Zhou, Sun, Yu, Xiao
arxiv.org/abs/2509.23392 mastoxiv.page/@arXiv_csAI_bot/
- Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models
Leander Girrbach, Stephan Alaniz, Genevieve Smith, Trevor Darrell, Zeynep Akata
arxiv.org/abs/2510.03721 mastoxiv.page/@arXiv_csCV_bot/
- Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Zhang, Hu, Upasani, Ma, Hong, Kamanuru, Rainton, Wu, Ji, Li, Thakker, Zou, Olukotun
arxiv.org/abs/2510.04618 mastoxiv.page/@arXiv_csLG_bot/
- Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Giannone, Xu, Nayak, Awhad, Sudalairaj, Xu, Srivastava
arxiv.org/abs/2510.05825 mastoxiv.page/@arXiv_csLG_bot/
- Complete asymptotic type-token relationship for growing complex systems with inverse power-law co...
Pablo Rosillo-Rodes, Laurent H\'ebert-Dufresne, Peter Sheridan Dodds
arxiv.org/abs/2511.02069 mastoxiv.page/@arXiv_physicsso
- ViPRA: Video Prediction for Robot Actions
Sandeep Routray, Hengkai Pan, Unnat Jain, Shikhar Bahl, Deepak Pathak
arxiv.org/abs/2511.07732 mastoxiv.page/@arXiv_csRO_bot/
- AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
Chandrachur Bhattacharya, Sibendu Som
arxiv.org/abs/2511.14043
- VideoARM: Agentic Reasoning over Hierarchical Memory for Long-Form Video Understanding
Yufei Yin, Qianke Meng, Minghao Chen, Jiajun Ding, Zhenwei Shao, Zhou Yu
arxiv.org/abs/2512.12360 mastoxiv.page/@arXiv_csCV_bot/
- RadImageNet-VQA: A Large-Scale CT and MRI Dataset for Radiologic Visual Question Answering
L\'eo Butsanets, Charles Corbi\`ere, Julien Khlaut, Pierre Manceron, Corentin Dancette
arxiv.org/abs/2512.17396 mastoxiv.page/@arXiv_csCV_bot/
- Measuring all the noises of LLM Evals
Sida Wang
arxiv.org/abs/2512.21326 mastoxiv.page/@arXiv_csLG_bot/
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@arXiv_csLG_bot@mastoxiv.page
2026-02-25 16:08:18

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[5/6]:
- Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
Apurv Verma, NhatHai Phan, Shubhendu Trivedi
arxiv.org/abs/2506.04462 mastoxiv.page/@arXiv_csCL_bot/
- Sensory-Motor Control with Large Language Models via Iterative Policy Refinement
J\^onata Tyska Carvalho, Stefano Nolfi
arxiv.org/abs/2506.04867 mastoxiv.page/@arXiv_csAI_bot/
- 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
arxiv.org/abs/2506.13792 mastoxiv.page/@arXiv_csAI_bot/
- Feedback-driven recurrent quantum neural network universality
Lukas Gonon, Rodrigo Mart\'inez-Pe\~na, Juan-Pablo Ortega
arxiv.org/abs/2506.16332 mastoxiv.page/@arXiv_quantph_b
- Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
Cook, Sapora, Ahmadian, Khan, Rocktaschel, Foerster, Ruis
arxiv.org/abs/2506.18777 mastoxiv.page/@arXiv_csAI_bot/
- Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning
Jiechen Chen, Bipin Rajendran, Osvaldo Simeone
arxiv.org/abs/2506.21324 mastoxiv.page/@arXiv_csNE_bot/
- Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
Pierre Boudart (SIERRA), Pierre Gaillard (Thoth), Alessandro Rudi (PSL, DI-ENS, Inria)
arxiv.org/abs/2507.05306 mastoxiv.page/@arXiv_statML_bo
- Characterizing State Space Model and Hybrid Language Model Performance with Long Context
Saptarshi Mitra, Rachid Karami, Haocheng Xu, Sitao Huang, Hyoukjun Kwon
arxiv.org/abs/2507.12442 mastoxiv.page/@arXiv_csAR_bot/
- 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
arxiv.org/abs/2507.19575 mastoxiv.page/@arXiv_csCV_bot/
- TASER: Table Agents for Schema-guided Extraction and Recommendation
Nicole Cho, Kirsty Fielding, William Watson, Sumitra Ganesh, Manuela Veloso
arxiv.org/abs/2508.13404 mastoxiv.page/@arXiv_csAI_bot/
- Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
Nuno Costa, Julija Zavadlav
arxiv.org/abs/2509.02060 mastoxiv.page/@arXiv_qbioBM_bo
- PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models
Jeongjae Lee, Jong Chul Ye
arxiv.org/abs/2509.25774 mastoxiv.page/@arXiv_csCV_bot/
- 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
arxiv.org/abs/2510.06868 mastoxiv.page/@arXiv_csIT_bot/
- MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile...
Chengshu Li, et al.
arxiv.org/abs/2510.18316 mastoxiv.page/@arXiv_csRO_bot/
- A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz
arxiv.org/abs/2510.20954 mastoxiv.page/@arXiv_statML_bo
- Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
Bazinska, Mathys, Casucci, Rojas-Carulla, Davies, Souly, Pfister
arxiv.org/abs/2510.22620 mastoxiv.page/@arXiv_csCR_bot/
- Uncertainty Calibration of Multi-Label Bird Sound Classifiers
Raphael Schwinger, Ben McEwen, Vincent S. Kather, Ren\'e Heinrich, Lukas Rauch, Sven Tomforde
arxiv.org/abs/2511.08261 mastoxiv.page/@arXiv_csSD_bot/
- Two-dimensional RMSD projections for reaction path visualization and validation
Rohit Goswami (Institute IMX and Lab-COSMO, \'Ecole polytechnique f\'ed\'erale de Lausanne)
arxiv.org/abs/2512.07329 mastoxiv.page/@arXiv_physicsch
- Distribution-informed Online Conformal Prediction
Dongjian Hu, Junxi Wu, Shu-Tao Xia, Changliang Zou
arxiv.org/abs/2512.07770 mastoxiv.page/@arXiv_statML_bo
- Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss
Ang Lv, Jin Ma, Yiyuan Ma, Siyuan Qiao
arxiv.org/abs/2512.23447 mastoxiv.page/@arXiv_csCL_bot/
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@mgorny@social.treehouse.systems
2026-01-18 18:04:19

Cynicism, "AI"
I've been pointed out the "Reflections on 2025" post by Samuel Albanie [1]. The author's writing style makes it quite a fun, I admit.
The first part, "The Compute Theory of Everything" is an optimistic piece on "#AI". Long story short, poor "AI researchers" have been struggling for years because of predominant misconception that "machines should have been powerful enough". Fortunately, now they can finally get their hands on the kind of power that used to be only available to supervillains, and all they have to do is forget about morals, agree that their research will be used to murder millions of people, and a few more millions will die as a side effect of the climate crisis. But I'm digressing.
The author is referring to an essay by Hans Moravec, "The Role of Raw Power in Intelligence" [2]. It's also quite an interesting read, starting with a chapter on how intelligence evolved independently at least four times. The key point inferred from that seems to be, that all we need is more computing power, and we'll eventually "brute-force" all AI-related problems (or die trying, I guess).
As a disclaimer, I have to say I'm not a biologist. Rather just a random guy who read a fair number of pieces on evolution. And I feel like the analogies brought here are misleading at best.
Firstly, there seems to be an assumption that evolution inexorably leads to higher "intelligence", with a certain implicit assumption on what intelligence is. Per that assumption, any animal that gets "brainier" will eventually become intelligent. However, this seems to be missing the point that both evolution and learning doesn't operate in a void.
Yes, many animals did attain a certain level of intelligence, but they attained it in a long chain of development, while solving specific problems, in specific bodies, in specific environments. I don't think that you can just stuff more brains into a random animal, and expect it to attain human intelligence; and the same goes for a computer — you can't expect that given more power, algorithms will eventually converge on human-like intelligence.
Secondly, and perhaps more importantly, what evolution did succeed at first is achieving neural networks that are far more energy efficient than whatever computers are doing today. Even if indeed "computing power" paved the way for intelligence, what came first is extremely efficient "hardware". Nowadays, human seem to be skipping that part. Optimizing is hard, so why bother with it? We can afford bigger data centers, we can afford to waste more energy, we can afford to deprive people of drinking water, so let's just skip to the easy part!
And on top of that, we're trying to squash hundreds of millions of years of evolution into… a decade, perhaps? What could possibly go wrong?
[1] #NoAI #NoLLM #LLM

@arXiv_csLG_bot@mastoxiv.page
2026-02-25 16:07:58

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[3/6]:
- Towards Scalable Oversight via Partitioned Human Supervision
Ren Yin, Takashi Ishida, Masashi Sugiyama
arxiv.org/abs/2510.22500 mastoxiv.page/@arXiv_csLG_bot/
- ContextPilot: Fast Long-Context Inference via Context Reuse
Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai
arxiv.org/abs/2511.03475 mastoxiv.page/@arXiv_csLG_bot/
- Metabolomic Biomarker Discovery for ADHD Diagnosis Using Interpretable Machine Learning
Nabil Belacel, Mohamed Rachid Boulassel
arxiv.org/abs/2601.11283 mastoxiv.page/@arXiv_csLG_bot/
- PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction
Akila Sampath, Vandana Janeja, Jianwu Wang
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
arxiv.org/abs/2602.03596
- LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordina...
Anand, Helbling, Davenport, Berman, Alagapan, Rozell
arxiv.org/abs/2602.04192
- Towards Robust Scaling Laws for Optimizers
Alexandra Volkova, Mher Safaryan, Christoph H. Lampert, Dan Alistarh
arxiv.org/abs/2602.07712 mastoxiv.page/@arXiv_csLG_bot/
- 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
arxiv.org/abs/2602.07729 mastoxiv.page/@arXiv_csLG_bot/
- AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine L...
Yuzhu Cai, Zexi Liu, Xinyu Zhu, Cheng Wang, Siheng Chen
arxiv.org/abs/2602.07906 mastoxiv.page/@arXiv_csLG_bot/
- VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training
Guobin Shen, Chenxiao Zhao, Xiang Cheng, Lei Huang, Xing Yu
arxiv.org/abs/2602.10693 mastoxiv.page/@arXiv_csLG_bot/
- 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
arxiv.org/abs/2602.11184 mastoxiv.page/@arXiv_csLG_bot/
- MUSE: Multi-Tenant Model Serving With Seamless Model Updates
Correia, Ferreira, Martins, Bento, Guerreiro, Pereira, Gomes, Bono, Ferreira, Bizarro
arxiv.org/abs/2602.11776 mastoxiv.page/@arXiv_csLG_bot/
- Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
Jorge Carrasco-Pollo, Floor Eijkelboom, Jan-Willem van de Meent
arxiv.org/abs/2602.13813 mastoxiv.page/@arXiv_csLG_bot/
- 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
arxiv.org/abs/2602.14462 mastoxiv.page/@arXiv_csLG_bot/
- Divine Benevolence is an $x^2$: GLUs scale asymptotically faster than MLPs
Alejandro Francisco Queiruga
arxiv.org/abs/2602.14495 mastoxiv.page/@arXiv_csLG_bot/
- \"UberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset
DatologyAI, et al.
arxiv.org/abs/2602.15210 mastoxiv.page/@arXiv_csLG_bot/
- GLM-5: from Vibe Coding to Agentic Engineering
GLM-5-Team, et al.
arxiv.org/abs/2602.15763 mastoxiv.page/@arXiv_csLG_bot/
- Anatomy of Capability Emergence: Scale-Invariant Representation Collapse and Top-Down Reorganizat...
Jayadev Billa
arxiv.org/abs/2602.15997 mastoxiv.page/@arXiv_csLG_bot/
- AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models
KC Santosh, Srikanth Baride, Rodrigue Rizk
arxiv.org/abs/2602.16042 mastoxiv.page/@arXiv_csLG_bot/
- 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
arxiv.org/abs/2602.16947 mastoxiv.page/@arXiv_csLG_bot/
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