Tootfinder

This https://arxiv.org/abs/2405.03306 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum advantage in batteries for Sachdev-Ye-Kitaev interactions
A quantum advantage can be achieved in the unitary charging of quantum batteries if their cells are interacting. Here, we try to clarify with some analytical calculations whether and how this quantum advantage is achieved for sparse Sachdev-Ye-Kitaev interactions. By performing a simple modelization, we find that for $q$-point rescaled sparse SYK interactions the quantum advantage goes as $Γ\sim N^{\fracα{q}-\frac{1}{2}}$, where $α$ is related to the connectivity and $N$ is the number of cel…

Drake doesn't like Kendrick Lamar, and Kendrick Lamar doesn't like Drake. That is all ye know, and that is all ye need to know.

SAT-DIFF: A Tree Diffing Framework Using SAT Solving
Chuqin Geng, Haolin Ye, Yihan Zhang, Brigitte Pientka, Xujie Si
https://arxiv.org/abs/2404.04731 https…

SAT-DIFF: A Tree Diffing Framework Using SAT Solving
Computing differences between tree-structured data is a critical but challenging problem in software analysis. In this paper, we propose a novel tree diffing approach called SatDiff, which reformulates the structural diffing problem into a MaxSAT problem. By encoding the necessary transformations from the source tree to the target tree, SatDiff generates correct, minimal, and type safe low-level edit scripts with formal guarantees. We then synthesize concise high-level edit scripts by effective…

pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving
Wei-Bin Kou, Qingfeng Lin, Ming Tang, Sheng Xu, Rongguang Ye, Yang Leng, Shuai Wang, Zhenyu Chen, Guangxu Zhu, Yik-Chung Wu
https://arxiv.org/abs/2405.04146…

Language Models as Critical Thinking Tools: A Case Study of Philosophers
Andre Ye, Jared Moore, Rose Novick, Amy X. Zhang
https://arxiv.org/abs/2404.04516 …

Language Models as Critical Thinking Tools: A Case Study of Philosophers
Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find…

PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy
Yulian Mao, Qingqing Ye, Haibo Hu, Qi Wang, Kai Huang
https://arxiv.org/abs/2404.03873

PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy
Time series have numerous applications in finance, healthcare, IoT, and smart city. In many of these applications, time series typically contain personal data, so privacy infringement may occur if they are released directly to the public. Recently, local differential privacy (LDP) has emerged as the state-of-the-art approach to protecting data privacy. However, existing works on LDP-based collections cannot preserve the shape of time series. A recent work, PatternLDP, attempts to address this p…

This https://arxiv.org/abs/2402.17824 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Quantum glasses, reparameterization invariance, Sachdev-Ye-Kitaev models
A brief survey of some random quantum models with infinite-range couplings is presented. Insights from such models have led to advances in the quantum theory of charged black holes in spatial dimensions $d \geq 3$, and to a universal theory of strange metals in correlated electron materials in $d=2$; these are also briefly reviewed.

Efficient and Provably Convergent Computation of Information Bottleneck: A Semi-Relaxed Approach
Lingyi Chen, Shitong Wu, Jiachuan Ye, Huihui Wu, Wenyi Zhang, Hao Wu
https://arxiv.org/abs/2404.04862

Efficient and Provably Convergent Computation of Information Bottleneck: A Semi-Relaxed Approach
Information Bottleneck (IB) is a technique to extract information about one target random variable through another relevant random variable. This technique has garnered significant interest due to its broad applications in information theory and deep learning. Hence, there is a strong motivation to develop efficient numerical methods with high precision and theoretical convergence guarantees. In this paper, we propose a semi-relaxed IB model, where the Markov chain and transition probability co…

🔊 #NowPlaying on fip
Quantic & Nidia Gongora & Quantic & Nidia Gongora:
🎵 E ye ye (radio edit)
#Quantic #NidiaGongora
https://quanticmusic.bandcamp.com/album/e-ye-ye

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement
Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao
https://arxiv.org/abs/2404.04481 <…

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement
Cross-Domain Recommendation (CDR) seeks to enable effective knowledge transfer across domains. Existing works rely on either representation alignment or transformation bridges, but they struggle on identifying domain-shared from domain-specific latent factors. Specifically, while CDR describes user representations as a joint distribution over two domains, these methods fail to account for its joint identifiability as they primarily fixate on the marginal distribution within a particular domain.…

Contouring Error Bounded Control for Biaxial Switched Linear Systems
Meng Yuan, Ye Wang, Chris Manzie, Zhezhuang Xu, Tianyou Chai
https://arxiv.org/abs/2404.05404

Contouring Error Bounded Control for Biaxial Switched Linear Systems
Biaxial motion control systems are used extensively in manufacturing and printing industries. To improve throughput and reduce machine cost, lightweight materials are being proposed in structural components but may result in higher flexibility in the machine links. This flexibility is often position dependent and compromises precision of the end effector of the machine. To address the need for improved contouring accuracy in industrial machines with position-dependent structural flexibility, th…

Exploring the Impact of Opinion Polarization on Short Video Consumption
Bangde Du, Ziyi Ye, Zhijing Wu, Qingyao Ai, Yiqun Liu
https://arxiv.org/abs/2403.04184

Exploring the Impact of Opinion Polarization on Short Video Consumption
Investigating the increasingly popular domain of short video consumption, this study focuses on the impact of Opinion Polarization (OP), a significant factor in the digital landscape influencing public opinions and social interactions. We analyze OP's effect on viewers' perceptions and behaviors, finding that traditional feedback metrics like likes and watch time fail to fully capture and measure OP. Addressing this gap, our research utilizes Electroencephalogram (EEG) signals to introduce a no…

Direct Training High-Performance Deep Spiking Neural Networks: A Review of Theories and Methods
Chenlin Zhou, Han Zhang, Liutao Yu, Yumin Ye, Zhaokun Zhou, Liwei Huang, Zhengyu Ma, Xiaopeng Fan, Huihui Zhou, Yonghong Tian
https://arxiv.org/abs/2405.04289

Direct Training High-Performance Deep Spiking Neural Networks: A Review of Theories and Methods
Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal dynamics, and event-driven computation. The direct training algorithms based on the surrogate gradient method provide sufficient flexibility to design novel SNN architectures and explore the spatial-temporal dynamics of SNNs. According to previous studies, the performance of models is highly dependent on their …

GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling
Runzhen Xue, Mingyu Yan, Dengke Han, Yihan Teng, Zhimin Tang, Xiaochun Ye, Dongrui Fan
https://arxiv.org/abs/2404.04792

GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling
Heterogeneous Graph Neural Networks (HGNNs) have broadened the applicability of graph representation learning to heterogeneous graphs. However, the irregular memory access pattern of HGNNs leads to the buffer thrashing issue in HGNN accelerators. In this work, we identify an opportunity to address buffer thrashing in HGNN acceleration through an analysis of the topology of heterogeneous graphs. To harvest this opportunity, we propose a graph restructuring method and map it into a hardware front…

On the Classification of Finite Quasi-Quantum Groups over Abelian Groups
Hua-Lin Huang, Gongxiang Liu, Yuping Yang, Yu Ye
https://arxiv.org/abs/2403.04455 …

On the Classification of Finite Quasi-Quantum Groups over Abelian Groups
Using a variety of methods developed in the theory of finite-dimensional quasi-Hopf algebras, we classify all finite-dimensional coradically graded pointed coquasi-Hopf algebras over abelian groups. As a consequence, we partially confirm the generation conjecture of pointed finite tensor categories due to Etingof, Gelaki, Nikshych and Ostrik.

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Sch\"onlieb
https://arxiv.org/abs/2404.05445

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation
Unsupervised learning is a training approach in the situation where ground truth data is unavailable, such as inverse imaging problems. We present an unsupervised Bayesian training approach to learning convex neural network regularizers using a fixed noisy dataset, based on a dual Markov chain estimation method. Compared to classical supervised adversarial regularization methods, where there is access to both clean images as well as unlimited to noisy copies, we demonstrate close performance on…

An interview with Andrew Bosworth on the 10th anniversary of Reality Labs, the past and future of VR/AR/AI, Meta's next AR glasses prototype, and more (Scott Stein/CNET)
https://www.cnet.com/tech/computing/ten-years-aft…

10 Years After Facebook Bought Oculus, What's Next for Meta's VR Plans?
Meta CTO Andrew Bosworth talks with CNET about the past and future of VR, AR and AI.

SGNet: Folding Symmetrical Protein Complex with Deep Learning
Zhaoqun Li, Jingcheng Yu, Qiwei Ye
https://arxiv.org/abs/2403.04395 https://

SGNet: Folding Symmetrical Protein Complex with Deep Learning
Deep learning has made significant progress in protein structure prediction, advancing the development of computational biology. However, despite the high accuracy achieved in predicting single-chain structures, a significant number of large homo-oligomeric assemblies exhibit internal symmetry, posing a major challenge in structure determination. The performances of existing deep learning methods are limited since the symmetrical protein assembly usually has a long sequence, making structural c…

Valley edge states as bound states in the continuum
Shunda Yin, Liping Ye, Hailong He, Xueqin Huang, Manzhu Ke, Weiyin Deng, Jiuyang Lu, Zhengyou Liu
https://arxiv.org/abs/2404.05412

Valley edge states as bound states in the continuum
Bound states in the continuum (BICs) are spatially localized states with energy embedded in the continuum spectrum of extended states. The combination of BICs physics and nontrivial band topology theory giving rise to topological BICs, which are robust against disorders and meanwhile of the merit of conventional BICs, is attracting wide attention recently. Here, we report valley edge states as topological BICs, which appear at domain wall between two distinct valley topological phases. The robu…

A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations
Yijie Li, Wei Zhang, Ye Wu, Li Yin, Ce Zhu, Yuqian Chen, Suheyla Cetin-Karayumak, Kang Ik K Cho, Leo R. Zekelman, Jarrett Rushmore, Yogesh Rathi, Nikos Makris, Lauren J. O'Donnell, Fan Zhang
https://arxiv.org/abs/240…

A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations
The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population …

Computation and Critical Transitions of Rate-Distortion-Perception Functions With Wasserstein Barycenter
Chunhui Chen, Xueyan Niu, Wenhao Ye, Hao Wu, Bo Bai
https://arxiv.org/abs/2404.04681

Computation and Critical Transitions of Rate-Distortion-Perception Functions With Wasserstein Barycenter
The information rate-distortion-perception (RDP) function characterizes the three-way trade-off between description rate, average distortion, and perceptual quality measured by discrepancy between probability distributions. We study several variants of the RDP functions through the lens of optimal transport. By transforming the information RDP function into a Wasserstein Barycenter problem, we identify the critical transitions when one of the constraints becomes inactive and demonstrate several…

MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
Jianjian Cao, Peng Ye, Shengze Li, Chong Yu, Yansong Tang, Jiwen Lu, Tao Chen
https://arxiv.org/abs/2403.02991

MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
Vision-Language Transformers (VLTs) have shown great success recently, but are meanwhile accompanied by heavy computation costs, where a major reason can be attributed to the large number of visual and language tokens. Existing token pruning research for compressing VLTs mainly follows a single-modality-based scheme yet ignores the critical role of aligning different modalities for guiding the token pruning process, causing the important tokens for one modality to be falsely pruned in another m…

Zilber's Trichotomy in Hausdorff Geometric Structures
Benjamin Castle, Assaf Hasson, Jinhe Ye
https://arxiv.org/abs/2405.02209 https://

Zilber's Trichotomy in Hausdorff Geometric Structures
We give a new axiomatic treatment of the Zilber trichotomy, and use it to complete the proof of the trichotomy for relics of algebraically closed fields, i.e., reducts of the ACF-induced structure on ACF-definable sets. More precisely, we introduce a class of geometric structures equipped with a Hausdorff topology, called \textit{Hausdorff geometric structures}. Natural examples include the complex field; algebraically closed valued fields; o-minimal expansions of real closed fields; and charac…

The best whistler: a cavitating tip vortex
Zhaohui Qian, Weixiang Ye, Yongshun Zeng, Xiaoxing Peng, Xianwu Luo
https://arxiv.org/abs/2405.02886 https://

The best whistler: a cavitating tip vortex
The discrete tone radiated from a cavitating tip vortex, known as "vortex singing", was first recognized in 1989, but its sound generation mechanism has remained a mystery for over thirty years. In this letter, by means of the correction for the cavitation bubble dynamics and the dispersion relation of cavity interfacial waves, we found that after the far-end disturbances propagate upstream, the whistling vortex should be triggered by near-end sound sources, the breathing mode waves. Further ut…

🔊 #NowPlaying on #BBC6Music's #NewMusicFix
Kim Gordon:
🎵 BYE BYE
#KimGordon
https://open.spotify.com/track/4K2hu1I4tuRpgDLiNTTEi2
https://kimgordon.bandcamp.com/track/bye-bye

Simultaneous Localization and Recognition of Subwavelength Non-Cooperative Entities Based on SISO Time Reversal and Neural Networks
Yinchen Wang, Yu Duan, Yu-Qi Ye, Ren Wang, Biao Li, Bin Jiang, Xin Liu, Bing-Zhong Wang
https://arxiv.org/abs/2403.04150

Simultaneous Localization and Recognition of Subwavelength Non-Cooperative Entities Based on SISO Time Reversal and Neural Networks
The simultaneous localization and recognition of subwavelength non-cooperative entities within complex multi-scattering environments using a simplified system continues to pose a substantial challenge. This communication addresses this challenge by synergistically integrating time reversal time-frequency phase prints (TRTFPPs) and neural networks. Initially, a time reversal (TR) single-input single-output (SISO) framework is employed to generate TRTFPPs. Through the devised approach, two types …

Deep Space Separable Distillation for Lightweight Acoustic Scene Classification
ShuQi Ye, Yuan Tian
https://arxiv.org/abs/2405.03567 https://

Deep Space Separable Distillation for Lightweight Acoustic Scene Classification
Acoustic scene classification (ASC) is highly important in the real world. Recently, deep learning-based methods have been widely employed for acoustic scene classification. However, these methods are currently not lightweight enough as well as their performance is not satisfactory. To solve these problems, we propose a deep space separable distillation network. Firstly, the network performs high-low frequency decomposition on the log-mel spectrogram, significantly reducing computational comple…

Con stuff
At a local weeb con...damn the artist alley is such a dangerous place. So many amazing skilled artists, I wanna buy everything. 😭
(On the plus side, I now have a bunch of Hazbin merch heck ye)

Rescale-Invariant Federated Reinforcement Learning for Resource Allocation in V2X Networks
Kaidi Xu, Shenglong Zhou, Geoffrey Ye Li
https://arxiv.org/abs/2405.01961

Rescale-Invariant Federated Reinforcement Learning for Resource Allocation in V2X Networks
Federated Reinforcement Learning (FRL) offers a promising solution to various practical challenges in resource allocation for vehicle-to-everything (V2X) networks. However, the data discrepancy among individual agents can significantly degrade the performance of FRL-based algorithms. To address this limitation, we exploit the node-wise invariance property of ReLU-activated neural networks, with the aim of reducing data discrepancy to improve learning performance. Based on this property, we intr…

This says #NYC congestion pricing starts in June. I know better than to get my hopes up, but it would still be pretty nice if it did.
https://bird.makeup/users/streetsblogn

Streetsblog New York
Should we be concerned about fake tag$ as conge$tion pricing start$? Why, ye$: https://nyc.streetsblog.org/2024/02/29/on-eve-of-congestion-pricing-plate-scams-at-bridge-tolls-are-way-up

🔊 #NowPlaying on BBCRadio3's #ThroughTheNight
Ruth Watson Henderson, Claire Preston, Elmer Iseler Singers & Lydia Adams:
🎵 Sing All Ye Joyful for SATB with piano accompaniment
#RuthWatsonHenderson #ClairePreston #ElmerIselerSingers #LydiaAdams

SalienTime: User-driven Selection of Salient Time Steps for Large-Scale Geospatial Data Visualization
Juntong Chen, Haiwen Huang, Huayuan Ye, Zhong Peng, Chenhui Li, Changbo Wang
https://arxiv.org/abs/2403.03449

SalienTime: User-driven Selection of Salient Time Steps for Large-Scale Geospatial Data Visualization
The voluminous nature of geospatial temporal data from physical monitors and simulation models poses challenges to efficient data access, often resulting in cumbersome temporal selection experiences in web-based data portals. Thus, selecting a subset of time steps for prioritized visualization and pre-loading is highly desirable. Addressing this issue, this paper establishes a multifaceted definition of salient time steps via extensive need-finding studies with domain experts to understand thei…

AceMap: Knowledge Discovery through Academic Graph
Xinbing Wang, Luoyi Fu, Xiaoying Gan, Ying Wen, Guanjie Zheng, Jiaxin Ding, Liyao Xiang, Nanyang Ye, Meng Jin, Shiyu Liang, Bin Lu, Haiwen Wang, Yi Xu, Cheng Deng, Shao Zhang, Huquan Kang, Xingli Wang, Qi Li, Zhixin Guo, Jiexing Qi, Pan Liu, Yuyang Ren, Lyuwen Wu, Jungang Yang, Jianping Zhou, Chenghu Zhou

AceMap: Knowledge Discovery through Academic Graph
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering search results based on relational databases, they often neglect the analysis of collaborations between scientific entities and the evolution of ideas, as well as the in-depth analysis of content within scientific publications. The representation of heterogeneous graphs and the effective measurement, analysis, and mining …

This https://arxiv.org/abs/2403.01950 has been replaced.
link: https://scholar.google.com/scholar?q=a

From Chaos to Integrability in Double Scaled SYK
We study thermodynamic phase transitions between integrable and chaotic dynamics. We do so by analyzing models that interpolate between the chaotic double scaled Sachdev-Ye-Kitaev (SYK) and the integrable $p$-spin systems, in a limit where they are described by chord diagrams. We develop a path integral formalism by coarse graining over the diagrams, which we use to argue that the system has two distinct phases: one is continuously connected to the chaotic system, and the other to the integrabl…

NL2KQL: From Natural Language to Kusto Query
Amir H. Abdi, Xinye Tang, Jeremias Eichelbaum, Mahan Das, Alex Klein, Nihal Irmak Pakis, William Blum, Daniel L Mace, Tanvi Raja, Namrata Padmanabhan, Ye Xing
https://arxiv.org/abs/2404.02933

NL2KQL: From Natural Language to Kusto Query
Data is growing rapidly in volume and complexity. Proficiency in database query languages is pivotal for crafting effective queries. As coding assistants become more prevalent, there is significant opportunity to enhance database query languages. The Kusto Query Language (KQL) is a widely used query language for large semi-structured data such as logs, telemetries, and time-series for big data analytics platforms. This paper introduces NL2KQL an innovative framework that uses large language mod…

Quasi-diagrams and gentle algebras
Haigang Hu, Xiao-Chuang Wang, Yu Ye
https://arxiv.org/abs/2403.02986 https://arxiv.org/pdf/2403.02…

Quasi-diagrams and gentle algebras
Any gentle algebra $A$ with one maximal path corresponds to a unique quasi-diagram $α$. We introduce the regularity for $α$, and show that $A$ has finite global dimension if and only if $α$ is regular. We characterize regular quasi-diagrams which remain regular under the dihedral group action. We prove that the set of maximal chord diagrams is the "biggest" one among the sets closed under taking Koszul dual and rotations.

Zilber's Trichotomy in Hausdorff Geometric Structures
Benjamin Castle, Assaf Hasson, Jinhe Ye
https://arxiv.org/abs/2405.02209 https://

Zilber's Trichotomy in Hausdorff Geometric Structures
We give a new axiomatic treatment of the Zilber trichotomy, and use it to complete the proof of the trichotomy for relics of algebraically closed fields, i.e., reducts of the ACF-induced structure on ACF-definable sets. More precisely, we introduce a class of geometric structures equipped with a Hausdorff topology, called \textit{Hausdorff geometric structures}. Natural examples include the complex field; algebraically closed valued fields; o-minimal expansions of real closed fields; and charac…

Verified. 10 years of Revolution of Dignity. RUSpropaganda Rhetoric, debunked Written by Anastasiia Ratieieva, analyst, HWAG/UCMC Propaganda Digest: This is our weekly analysis that exposes the most e Source : https://uacrisis.org/en/verified-10-ye

MetaRM: Shifted Distributions Alignment via Meta-Learning
Shihan Dou, Yan Liu, Enyu Zhou, Tianlong Li, Haoxiang Jia, Limao Xiong, Xin Zhao, Junjie Ye, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
https://arxiv.org/abs/2405.00438

MetaRM: Shifted Distributions Alignment via Meta-Learning
The success of Reinforcement Learning from Human Feedback (RLHF) in language model alignment is critically dependent on the capability of the reward model (RM). However, as the training process progresses, the output distribution of the policy model shifts, leading to the RM's reduced ability to distinguish between responses. This issue is further compounded when the RM, trained on a specific data distribution, struggles to generalize to examples outside of that distribution. These two issues c…

The best whistler: a cavitating tip vortex
Zhaohui Qian, Weixiang Ye, Yongshun Zeng, Xiaoxing Peng, Xianwu Luo
https://arxiv.org/abs/2405.02886 https://

The best whistler: a cavitating tip vortex
The discrete tone radiated from a cavitating tip vortex, known as "vortex singing", was first recognized in 1989, but its sound generation mechanism has remained a mystery for over thirty years. In this letter, by means of the correction for the cavitation bubble dynamics and the dispersion relation of cavity interfacial waves, we found that after the far-end disturbances propagate upstream, the whistling vortex should be triggered by near-end sound sources, the breathing mode waves. Further ut…

🔊 #NowPlaying on #BBC6Music's #NewMusicFix
Kim Gordon:
🎵 BYE BYE
#KimGordon
https://open.spotify.com/track/4K2hu1I4tuRpgDLiNTTEi2
https://kimgordon.bandcamp.com/track/bye-bye

Biden restores endangered species protections rolled back by Trump
https://post.news/@/reuters/2eKhU6k4d47c6VCrg6Ru6i0hyYM

Biden restores endangered species protections rolled back by Trump
By: Rich McKay (Reuters) -The Biden administration on Thursday restored some protections under the Endangered Species Act rolled back under former President Donald Trump, giving the federal government more leeway to designate plants or animals as threatened or endangered. The 51-ye

Con stuff
At a local weeb con...damn the artist alley is such a dangerous place. So many amazing skilled artists, I wanna buy everything. 😭
(On the plus side, I now have a bunch of Hazbin merch heck ye)

Giant and controllable nonlinear magneto-optical effects in two-dimensional magnets
Dezhao Wu, Meng Ye, Haowei Chen, Yong Xu, Wenhui Duan
https://arxiv.org/abs/2404.03203

Giant and controllable nonlinear magneto-optical effects in two-dimensional magnets
The interplay of polarization and magnetism in materials with light can create rich nonlinear magneto-optical (NLMO) effects, and the recent discovery of two-dimensional (2D) van der Waals magnets provides remarkable control over NLMO effects due to their superb tunability. Here, based on first-principles calculations, we reported giant NLMO effects in CrI3-based 2D magnets, including a dramatic change of second-harmonics generation (SHG) polarization direction (90 degrees) and intensity (on/of…

Processing Load Allocation of On-Board Multi-User Detection for Payload-Constrained Satellite Networks
Sirui Miao, Neng Ye, Peisen Wang, Qiaolin Ouyang
https://arxiv.org/abs/2403.03635

Processing Load Allocation of On-Board Multi-User Detection for Payload-Constrained Satellite Networks
The rapid advance of mega-constellation facilitates the booming of direct-to-satellite massive access, where multi-user detection is critical to alleviate the induced inter-user interference. While centralized implementation of on-board detection induces unaffordable complexity for a single satellite, this paper proposes to allocate the processing load among cooperative satellites for finest exploitation of distributed processing power. Observing the inherent disparities among users, we first e…

GMMCalib: Extrinsic Calibration of LiDAR Sensors using GMM-based Joint Registration
Ilir Tahiraj, Felix Fent, Philipp Hafemann, Egon Ye, Markus Lienkamp
https://arxiv.org/abs/2404.03427

GMMCalib: Extrinsic Calibration of LiDAR Sensors using GMM-based Joint Registration
State-of-the-art LiDAR calibration frameworks mainly use non-probabilistic registration methods such as Iterative Closest Point (ICP) and its variants. These methods suffer from biased results due to their pair-wise registration procedure as well as their sensitivity to initialization and parameterization. This often leads to misalignments in the calibration process. Probabilistic registration methods compensate for these drawbacks by specifically modeling the probabilistic nature of the observ…

Dual-Role AoI-based Incentive Mechanism for HD map Crowdsourcing
Wentao Ye, Bo Liu, Yuan Luo, Jianwei Huang
https://arxiv.org/abs/2405.00353 https://

Dual-Role AoI-based Incentive Mechanism for HD map Crowdsourcing
A high-quality fresh high-definition (HD) map is vital in enhancing transportation efficiency and safety in autonomous driving. Vehicle-based crowdsourcing offers a promising approach for updating HD maps. However, recruiting crowdsourcing vehicles involves making the challenging tradeoff between the HD map freshness and recruitment costs. Existing studies on HD map crowdsourcing often (1) prioritize maximizing spatial coverage and (2) overlook the dual role of crowdsourcing vehicles in HD maps…

Backfire Effect Reveals Early Controversy in Online Media
Songtao Peng, Chenbo Fua, Han Han, Ye Wu, Kailun Zhu, Qi Xuan, Yong Min
https://arxiv.org/abs/2403.02708

Backfire Effect Reveals Early Controversy in Online Media
The rapid development of online media has significantly facilitated the public's information consumption, knowledge acquisition, and opinion exchange. However, it has also led to more violent conflicts in online discussions. Therefore, controversy detection becomes important for computational and social sciences. Previous research on detection methods has primarily focused on larger datasets and more complex computational models but has rarely examined the underlying mechanisms of conflict, par…

Lancet: Accelerating Mixture-of-Experts Training via Whole Graph Computation-Communication Overlapping
Chenyu Jiang, Ye Tian, Zhen Jia, Shuai Zheng, Chuan Wu, Yida Wang
https://arxiv.org/abs/2404.19429

Lancet: Accelerating Mixture-of-Experts Training via Whole Graph Computation-Communication Overlapping
The Mixture-of-Expert (MoE) technique plays a crucial role in expanding the size of DNN model parameters. However, it faces the challenge of extended all-to-all communication latency during the training process. Existing methods attempt to mitigate this issue by overlapping all-to-all with expert computation. Yet, these methods frequently fall short of achieving sufficient overlap, consequently restricting the potential for performance enhancements. In our study, we extend the scope of this cha…

Bipartite Sachdev-Ye Models with Read-Saleur Symmetries
J. Classen-Howes, P. Fendley, A. Pandey, S. A. Parameswaran
https://arxiv.org/abs/2403.15270 https:…

Bipartite Sachdev-Ye Models with Read-Saleur Symmetries
We introduce an SU(M)-symmetric disordered bipartite spin model with unusual characteristics. Although superficially similar to the Sachdev-Ye model, it has several markedly different properties for M>2. In particular, it has a large non-trivial nullspace whose dimension grows exponentially with system size. The states in this nullspace are frustration-free, and are ground states when the interactions are ferromagnetic. The exponential growth of the nullspace leads to Hilbert-space fragmentatio…

On manifolds with nonnegative Ricci curvature and the infimum of volume growth order $<2$
Zhu Ye
https://arxiv.org/abs/2405.00852 https://

On manifolds with nonnegative Ricci curvature and the infimum of volume growth order $<2$
We prove two rigidity theorems for open (complete and noncompact) $n$-manifolds $M$ with nonnegative Ricci curvature and the infimum of volume growth order $<2$. The first theorem asserts that the Riemannian universal cover of $M$ has Euclidean volume growth if and only if $M$ is flat with an $n-1$ dimensional soul. The second theorem asserts that there exists a nonconstant linear growth harmonic function on $M$ if and only if $M$ is isometric to the metric product $\mathbb{R}\times N$ for some…

Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models
Jiachen Ma, Anda Cao, Zhiqing Xiao, Jie Zhang, Chao Ye, Junbo Zhao
https://arxiv.org/abs/2404.02928

Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models
The fast advance of the image generation community has attracted attention worldwide. The safety issue needs to be further scrutinized and studied. There have been a few works around this area mostly achieving a post-processing design, model-specific, or yielding suboptimal image quality generation. Despite that, in this article, we discover a black-box attack method that enjoys three merits. It enables (i)-attacks both directed and semantic-driven that theoretically and practically pose a haza…

Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model
Danilo Bernardo, Xihe Xie, Parul Verma, Jonathan Kim, Virginia Liu, Ye Wu, Pew-Thian Yap, Srikantan Nagarajan, Ashish Raj
https://arxiv.org/abs/2405.02524

Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model
The spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unknown. To gain mechanistic insights into this process, we evaluate developmental EEG spectral changes via Bayesian model inversion of the spectral graph model (SGM), a parsimonious model of whole-brain spatiospectral activity derived from linearized neural field models coupled by the structural connectome. Simulation-bas…

Enhancing Credit Card Fraud Detection A Neural Network and SMOTE Integrated Approach
Mengran Zhu, Ye Zhang, Yulu Gong, Changxin Xu, Yafei Xiang
https://arxiv.org/abs/2405.00026

Enhancing Credit Card Fraud Detection A Neural Network and SMOTE Integrated Approach
Credit card fraud detection is a critical challenge in the financial sector, demanding sophisticated approaches to accurately identify fraudulent transactions. This research proposes an innovative methodology combining Neural Networks (NN) and Synthet ic Minority Over-sampling Technique (SMOTE) to enhance the detection performance. The study addresses the inherent imbalance in credit card transaction data, focusing on technical advancements for robust and precise fraud detection. Results demons…

Measurement of Milli-Charged Particles with a moderately large cross section from the Earth's core at IceCube
Ye Xu
https://arxiv.org/abs/2405.00060 ht…

Measurement of Milli-Charged Particles with a moderately large cross section from the Earth's core at IceCube
It is assumed that heavy dark matter $ϕ$ with O(TeV) mass captured by the Earth may decay to relativistic light milli-charged particles (MCPs). These MCPs could be measured by the IceCube neutrino telescope. The massless hidden photon model was taken for MCPs to interact with nuclei, so that the numbers and fluxes of expected MCPs may be evaluated at IceCube. Meanwhile, the numbers of expected neutrino background events were also evaluated at IceCube. Based on the assumption that no events are…

Extending Llama-3's Context Ten-Fold Overnight
Peitian Zhang, Ninglu Shao, Zheng Liu, Shitao Xiao, Hongjin Qian, Qiwei Ye, Zhicheng Dou
https://arxiv.org/abs/2404.19553 https://arxiv.org/pdf/2404.19553
arXiv:2404.19553v1 Announce Type: new
Abstract: We extend the context length of Llama-3-8B-Instruct from 8K to 80K via QLoRA fine-tuning. The entire training cycle is super efficient, which takes 8 hours on one 8xA800 (80G) GPU machine. The resulted model exhibits superior performances across a broad range of evaluation tasks, such as NIHS, topic retrieval, and long-context language understanding; meanwhile, it also well preserves the original capability over short contexts. The dramatic context extension is mainly attributed to merely 3.5K synthetic training samples generated by GPT-4 , which indicates the LLMs' inherent (yet largely underestimated) potential to extend its original context length. In fact, the context length could be extended far beyond 80K with more computation resources. Therefore, the team will publicly release the entire resources (including data, model, data generation pipeline, training code) so as to facilitate the future research from the community: \url{https://github.com/FlagOpen/FlagEmbedding}.

A fast cosine transformation accelerated method for predicting effective thermal conductivity
Changqing Ye, Shubin Fu, Eric T. Chung
https://arxiv.org/abs/2404.02433

A fast cosine transformation accelerated method for predicting effective thermal conductivity
Predicting effective thermal conductivity by solving a Partial Differential Equation (PDE) defined on a high-resolution Representative Volume Element (RVE) is a computationally intensive task. In this paper, we tackle the task by proposing an efficient and implementation-friendly computational method that can fully leverage the computing power offered by hardware accelerators, namely, graphical processing units (GPUs). We first employ the Two-Point Flux-Approximation scheme to discretize the PD…

Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check
Linhao Ye, Zhikai Lei, Jianghao Yin, Qin Chen, Jie Zhou, Liang He
https://arxiv.org/abs/2403.18243

Boosting Conversational Question Answering with Fine-Grained Retrieval-Augmentation and Self-Check
Retrieval-Augmented Generation (RAG) aims to generate more reliable and accurate responses, by augmenting large language models (LLMs) with the external vast and dynamic knowledge. Most previous work focuses on using RAG for single-round question answering, while how to adapt RAG to the complex conversational setting wherein the question is interdependent on the preceding context is not well studied. In this paper, we propose a conversation-level RAG approach, which incorporates fine-grained re…

Oh ye gods. What in the fresh hell is this? TEN PLUS TRO VIOLATIONS?
Fire the cops. Make them pay the damages out of their own pockets. The citizens of #Bellevue #Iowa shouldn't owe a dime.
#domesticviolence

After Iowa Police Ignored Her Pleas for Help, Her Estranged Husband Killed Her
Her family is now suing the city of Bellevue, Iowa, claiming that police inaction directly led to Angela Prichard's death.

A HAT Trick: Automatically Verifying Representation Invariants Using Symbolic Finite Automata
Zhe Zhou, Qianchuan Ye, Benjamin Delaware, Suresh Jagannathan
https://arxiv.org/abs/2404.01484

A HAT Trick: Automatically Verifying Representation Invariants Using Symbolic Finite Automata
Functional programs typically interact with stateful libraries that hide state behind typed abstractions. One particularly important class of applications are data structure implementations that rely on such libraries to provide a level of efficiency and scalability that may be otherwise difficult to achieve. However, because the specifications of the methods provided by these libraries are necessarily general and rarely specialized to the needs of any specific client, any required application-…

Primordial Black Hole Formation in a Dust Bouncing Model
E. J. Barroso, L. F. Dem\'etrio, S. D. P. Vitenti, Xuan Ye
https://arxiv.org/abs/2405.00207 ht…

Primordial Black Hole Formation in a Dust Bouncing Model
Linear scalar cosmological perturbations have increasing spectra in the contracting phase of bouncing models. We study the conditions for which these perturbations may collapse into primordial black holes and the hypothesis that these objects constitute a fraction of dark matter. We compute the critical density contrast that describes the collapse of matter perturbations in the flat-dust bounce model with a parametric solution, obtained from the Lemaitre-Tolman-Bondi metric that represents the …

GMMCalib: Extrinsic Calibration of LiDAR Sensors using GMM-based Joint Registration
Ilir Tahiraj, Felix Fent, Philipp Hafemann, Egon Ye, Markus Lienkamp
https://arxiv.org/abs/2404.03427

GMMCalib: Extrinsic Calibration of LiDAR Sensors using GMM-based Joint Registration
State-of-the-art LiDAR calibration frameworks mainly use non-probabilistic registration methods such as Iterative Closest Point (ICP) and its variants. These methods suffer from biased results due to their pair-wise registration procedure as well as their sensitivity to initialization and parameterization. This often leads to misalignments in the calibration process. Probabilistic registration methods compensate for these drawbacks by specifically modeling the probabilistic nature of the observ…

MetaRM: Shifted Distributions Alignment via Meta-Learning
Shihan Dou, Yan Liu, Enyu Zhou, Tianlong Li, Haoxiang Jia, Limao Xiong, Xin Zhao, Junjie Ye, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
https://arxiv.org/abs/2405.00438

MetaRM: Shifted Distributions Alignment via Meta-Learning
The success of Reinforcement Learning from Human Feedback (RLHF) in language model alignment is critically dependent on the capability of the reward model (RM). However, as the training process progresses, the output distribution of the policy model shifts, leading to the RM's reduced ability to distinguish between responses. This issue is further compounded when the RM, trained on a specific data distribution, struggles to generalize to examples outside of that distribution. These two issues c…

Lenovo beats estimates with Q3 revenue up 3% YoY to $15.72B after 5 quarters of decline and net income down 23% YoY to $337M; services revenue up 10% YoY to $2B (Josh Ye/Reuters)
https://www.reuters.com/technology/chinas-

This https://arxiv.org/abs/2310.12335 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Parisi's hypercube, Fock-space fluxes, and the microscopics of near-AdS$_2$/near-CFT$_1$ duality
Parisi's hypercube model describes a charged particle hopping on a $d$-dimensional hypercube with disordered background fluxes in the large $d$ limit. It was noted previously [Jia and Verbaarschot, J. High Energy Phys. 11 (2020) 154] that the hypercube model at leading order in $1/d$ has the same spectral density as the double-scaled Sachdev-Ye-Kitaev (DS-SYK) model. In this work we identify the set of observables that have the same correlation functions as the DS-SYK model, demonstrating that …

Room temperature Si:S barrier infrared detector with broadband response up to 4.4{\mu}m
He Zhu, Yunlong Xiao, Zhongyang Yu, Jiaqi Zhu, Qing Li, Zhenyu Ye, Xi Wang, Changlong Liu, Changyu Pan, Yufeng Shan, Junli Duan, Huizhen Wu, Weida Hu, Ning Dai
https://arxiv.org/abs/2405.02668

Room temperature Si:S barrier infrared detector with broadband response up to 4.4μm
Mid-infrared spectrum is a critical tool for chemical analysis, industrial inspection, environment, and other fields due to its rich chemical bond information. However, the complicated growth or fabrication procedures of existing mid-infrared sensitive materials hinder the large-scale production and utilization of mid-infrared detectors. To address this issue, we developed Si:S barrier detectors employing sulfur doped silicon and a sophisticated band barrier design. Since the transport of dark …

Effective Message Hiding with Order-Preserving Mechanisms
Gao Yu, Qiu Xuchong, Ye Zihan
https://arxiv.org/abs/2402.19160 https://arxi…

Effective Message Hiding with Order-Preserving Mechanisms
Message hiding, a technique that conceals secret message bits within a cover image, aims to achieve an optimal balance among message capacity, recovery accuracy, and imperceptibility. While convolutional neural networks have notably improved message capacity and imperceptibility, achieving high recovery accuracy remains challenging. This challenge arises because convolutional operations struggle to preserve the sequential order of message bits and effectively address the discrepancy between the…

🔊 #NowPlaying on fip
Nora Fischer & Marnix Dorrestein:
🎵 The fairy Queen Z 629 : Come all ye songsters (Acte II) Air de l'elfe - arrangement pour voix et guitare électrique
#NoraFischer #MarnixDorrestein

This https://arxiv.org/abs/2310.12335 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Parisi's hypercube, Fock-space fluxes, and the microscopics of near-AdS$_2$/near-CFT$_1$ duality
Parisi's hypercube model describes a charged particle hopping on a $d$-dimensional hypercube with disordered background fluxes in the large $d$ limit. It was noted previously [Jia and Verbaarschot, J. High Energy Phys. 11 (2020) 154] that the hypercube model at leading order in $1/d$ has the same spectral density as the double-scaled Sachdev-Ye-Kitaev (DS-SYK) model. In this work we identify the set of observables that have the same correlation functions as the DS-SYK model, demonstrating that …

Evolving Agents: Interactive Simulation of Dynamic and Diverse Human Personalities
Jiale Li, Jiayang Li, Jiahao Chen, Yifan Li, Shijie Wang, Hugo Zhou, Minjun Ye, Yunsheng Su
https://arxiv.org/abs/2404.02718

Evolving Agents: Interactive Simulation of Dynamic and Diverse Human Personalities
Human-like Agents with diverse and dynamic personality could serve as an important design probe in the process of user-centered design, thereby enabling designers to enhance the user experience of interactive application.In this article, we introduce Evolving Agents, a novel agent architecture that consists of two systems: Personality and Behavior. The Personality system includes three modules: Cognition, Emotion and Character Growth. The Behavior system comprises two modules: Planning and Acti…

Low-Overhead Defect-Adaptive Surface Code with Bandage-Like Super-Stabilizers
Zuolin Wei, Tan He, Yangsen Ye, Dachao Wu, Yiming Zhang, Youwei Zhao, Weiping Lin, He-Liang Huang, Xiaobo Zhu, Jian-Wei Pan
https://arxiv.org/abs/2404.18644

Low-Overhead Defect-Adaptive Surface Code with Bandage-Like Super-Stabilizers
To make practical quantum algorithms work, large-scale quantum processors protected by error-correcting codes are required to resist noise and ensure reliable computational outcomes. However, a major challenge arises from defects in processor fabrication, as well as occasional losses or cosmic rays during the computing process, all of which can lead to qubit malfunctions and disrupt error-correcting codes' normal operations. In this context, we introduce an automatic adapter to implement the su…

🔊 #NowPlaying on #BBC6Music's #6MusicFestivalLive
Kim Gordon:
🎵 BYE BYE
#KimGordon
https://open.spotify.com/track/4K2hu1I4tuRpgDLiNTTEi2
https://kimgordon.bandcamp.com/track/bye-bye

A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches
Zhigen Zhao, Shuo Chen, Yan Ding, Ziyi Zhou, Shiqi Zhang, Danfei Xu, Ye Zhao
https://arxiv.org/abs/2404.02817

A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches
Task and Motion Planning (TAMP) integrates high-level task planning and low-level motion planning to equip robots with the autonomy to effectively reason over long-horizon, dynamic tasks. Optimization-based TAMP focuses on hybrid optimization approaches that define goal conditions via objective functions and are capable of handling open-ended goals, robotic dynamics, and physical interaction between the robot and the environment. Therefore, optimization-based TAMP is particularly suited to solv…

Oh ye gods. What in the fresh hell is this? TEN PLUS TRO VIOLATIONS?
Fire the cops. Make them pay the damages out of their own pockets. The citizens of #Bellevue #Iowa shouldn't owe a dime.
#domesticviolence

After Iowa Police Ignored Her Pleas for Help, Her Estranged Husband Killed Her
Her family is now suing the city of Bellevue, Iowa, claiming that police inaction directly led to Angela Prichard's death.

BigGait: Learning Gait Representation You Want by Large Vision Models
Dingqiang Ye, Chao Fan, Jingzhe Ma, Xiaoming Liu, Shiqi Yu
https://arxiv.org/abs/2402.19122

BigGait: Learning Gait Representation You Want by Large Vision Models
Gait recognition stands as one of the most pivotal remote identification technologies and progressively expands across research and industrial communities. However, existing gait recognition methods heavily rely on task-specific upstream driven by supervised learning to provide explicit gait representations, which inevitably introduce expensive annotation costs and potentially cause cumulative errors. Escaping from this trend, this work explores effective gait representations based on the all-p…

Building defect conformal field theory from the Sachdev-Ye-Kitaev interactions
Yang Ge, Shao-Kai Jian
https://arxiv.org/abs/2403.18691 https://

Building defect conformal field theory from the Sachdev-Ye-Kitaev interactions
The coupling between defects and extended critical degrees of freedom gives rise to the intriguing theory known as defect conformal field theory (CFT). In this work, we introduce a novel family of boundary and interface CFTs by coupling $N$ Majorana chains with SYK$_q$ interactions at the defect. Our analysis reveals that the interaction with $q=2$ constitutes a new marginal defect. Employing a versatile saddle point method, we compute unique entanglement characterizations, including the $g$-fu…

Degradation Modeling and Prognostic Analysis Under Unknown Failure Modes
Ying Fu, Ye Kwon Huh, Kaibo Liu
https://arxiv.org/abs/2402.19294 https://

Robust Federated Contrastive Recommender System against Model Poisoning Attack
Wei Yuan, Chaoqun Yang, Liang Qu, Guanhua Ye, Quoc Viet Hung Nguyen, Hongzhi Yin
https://arxiv.org/abs/2403.20107

Robust Federated Contrastive Recommender System against Model Poisoning Attack
Federated Recommender Systems (FedRecs) have garnered increasing attention recently, thanks to their privacy-preserving benefits. However, the decentralized and open characteristics of current FedRecs present two dilemmas. First, the performance of FedRecs is compromised due to highly sparse on-device data for each client. Second, the system's robustness is undermined by the vulnerability to model poisoning attacks launched by malicious users. In this paper, we introduce a novel contrastive lea…

Enhancement of Magnon Transport by Superconductor Meissner Screening
Xi-Han Zhou, Xiyin Ye, Lihui Bai, Tao Yu
https://arxiv.org/abs/2404.02598 https://

Enhancement of Magnon Transport by Superconductor Meissner Screening
Recent experiments observe the spin-wave-Meissner-current modes in ferromagnetic insulator-superconductor heterostructures, in which the coherently excited spin waves seemingly do not decay as usual beneath the superconductor strip [Borst et al., Science 382, 430 (2023)]. We interpret this phenomenon by demonstrating that the stray magnetic field emitted by the magnetization dynamics is reflected, focused, and enhanced inside the ferromagnet by the supercurrent induced in the superconductor, su…

Evolving Agents: Interactive Simulation of Dynamic and Diverse Human Personalities
Jiale Li, Jiayang Li, Jiahao Chen, Yifan Li, Shijie Wang, Hugo Zhou, Minjun Ye, Yunsheng Su
https://arxiv.org/abs/2404.02718

Evolving Agents: Interactive Simulation of Dynamic and Diverse Human Personalities
Human-like Agents with diverse and dynamic personality could serve as an important design probe in the process of user-centered design, thereby enabling designers to enhance the user experience of interactive application.In this article, we introduce Evolving Agents, a novel agent architecture that consists of two systems: Personality and Behavior. The Personality system includes three modules: Cognition, Emotion and Character Growth. The Behavior system comprises two modules: Planning and Acti…

Hyperbolicity and model-complete fields
Micha{\l} Szachniewicz, Jinhe Ye
https://arxiv.org/abs/2403.15300 https://arxiv.org/pdf/2403.…

Hyperbolicity and model-complete fields
We study model-complete fields that avoid a given quasi-project variety $V$. There is a close connection between hyperbolicity of $V$ and the existence of the model companion for the theory of characteristic-zero fields without rational points on $V$, extending the results for curves by Will Johnson and Jinhe Ye. In particular, we show that if $V$ is a Brody hyperbolic projective variety over $\mathbb{Q}$ with $V(\mathbb{Q}) = \varnothing$, then the model companion, called $V\mathrm{XF}$, exist…

Probabilistic Semantic Communication over Wireless Networks with Rate Splitting
Zhouxiang Zhao, Zhaohui Yang, Ye Hu, Qianqian Yang, Wei Xu, Zhaoyang Zhang
https://arxiv.org/abs/2403.00434

Probabilistic Semantic Communication over Wireless Networks with Rate Splitting
In this paper, the problem of joint transmission and computation resource allocation for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. In the considered model, the base station (BS) needs to transmit a large amount of data to multiple users with RSMA. Due to limited communication resources, the BS is required to utilize semantic communication techniques to compress the large-sized data. The semantic communication is enabled by shar…

Baidu says that eight months after launch, its AI chatbot Ernie Bot now has 200M users and 85K enterprise clients, after reaching 100M users in December (Josh Ye/Reuters)
https://www.reuters.com/technology/baidu-says-a…

Quantum glasses, reparameterization invariance, Sachdev-Ye-Kitaev models
Subir Sachdev
https://arxiv.org/abs/2402.17824 https://arxiv…

Quantum glasses, reparameterization invariance, Sachdev-Ye-Kitaev models
A brief survey of some random quantum models with infinite-range couplings is presented. Insights from such models have led to advances in the quantum theory of charged black holes in spatial dimensions $d \geq 3$, and to a universal theory of strange metals in correlated electron materials in $d=2$; these are also briefly reviewed.

LOG-LIO2: A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis
Kai Huang, Junqiao Zhao, Jiaye Lin, Zhongyang Zhu, Shuangfu Song, Chen Ye, Tiantian Feng
https://arxiv.org/abs/2405.01316

LOG-LIO2: A LiDAR-Inertial Odometry with Efficient Uncertainty Analysis
Uncertainty in LiDAR measurements, stemming from factors such as range sensing, is crucial for LIO (LiDAR-Inertial Odometry) systems as it affects the accurate weighting in the loss function. While recent LIO systems address uncertainty related to range sensing, the impact of incident angle on uncertainty is often overlooked by the community. Moreover, the existing uncertainty propagation methods suffer from computational inefficiency. This paper proposes a comprehensive point uncertainty model…

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction
Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen
https://arxiv.org/abs/2403.18379

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction
Accurately estimating the Remaining Useful Life (RUL) of lithium-ion batteries is crucial for maintaining the safe and stable operation of rechargeable battery management systems. However, this task is often challenging due to the complex temporal dynamics involved. Recently, attention-based networks, such as Transformers and Informer, have been the popular architecture in time series forecasting. Despite their effectiveness, these models with abundant parameters necessitate substantial trainin…

An Expectation-Maximization Relaxed Method for Privacy Funnel
Lingyi Chen, Jiachuan Ye, Shitong Wu, Huihui Wu, Hao Wu, Wenyi Zhang
https://arxiv.org/abs/2405.00616

An Expectation-Maximization Relaxed Method for Privacy Funnel
The privacy funnel (PF) gives a framework of privacy-preserving data release, where the goal is to release useful data while also limiting the exposure of associated sensitive information. This framework has garnered significant interest due to its broad applications in characterization of the privacy-utility tradeoff. Hence, there is a strong motivation to develop numerical methods with high precision and theoretical convergence guarantees. In this paper, we propose a novel relaxation variant …

Entanglement entropy in type II$_1$ von Neumann algebra: examples in Double-Scaled SYK
Haifeng Tang
https://arxiv.org/abs/2404.02449 https://

Entanglement entropy in type II$_1$ von Neumann algebra: examples in Double-Scaled SYK
An intriguing feature of type II$_1$ von Neumann algebra is that the entropy of the mixed states is negative. Although the type classification of von Neumann algebra and its consequence in holography have been extensively explored recently, there has not been an explicit calculation of entropy in some physically interesting models with type II$_1$ algebra. In this paper, we study the entanglement entropy $S_n$ of the fixed length state $\{|n\rangle\}$ in Double-Scaled Sachdev-Ye-Kitaev mod…

Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering
Long Shi, Lei Cao, Yunshan Ye, Yu Zhao, Badong Chen
https://arxiv.org/abs/2403.18393

Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering
Graph learning is widely recognized as a crucial technique in multi-view clustering. Existing graph learning methods typically involve constructing an adaptive neighbor graph based on probabilistic neighbors and then learning a consensus graph to for clustering, however, they are confronted with two limitations. Firstly, they often rely on Euclidean distance to measure similarity when constructing the adaptive neighbor graph, which proves inadequate in capturing the intrinsic structure among da…

This https://arxiv.org/abs/2404.11436 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Excitation Transmission through a non-Hermitian traversable wormhole
This study explores the intricate real-time dynamics of a non-Hermitian system composed of two interconnected Sachdev-Ye-Kitaev (SYK) models. A central finding reveals that an excitation initially localized in the right SYK subsystem can be efficiently transmitted to the left subsystem subsequent to the characteristic scrambling time, a phenomenon facilitated by the intrinsic non-Hermitian nature of the system. The defining hallmark of non-Hermiticity is manifest in the asymmetric conveyance of…

This https://arxiv.org/abs/2403.13186 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Towards complexity in de Sitter space from the doubled-scaled Sachdev-Ye-Kitaev model
How can we define complexity in dS space from microscopic principles? Based on recent developments pointing towards a correspondence between a pair of double-scaled Sachdev-Ye-Kitaev (DSSYK) models/ 2D Liouville-de Sitter (LdS$_2$) field theory/ 3D Schwarzschild de Sitter (SdS$_3$) space in arXiv:2310.16994, arXiv:2402.00635, arXiv:2402.02584, we study concrete complexity proposals in the microscopic models and their dual descriptions. First, we examine the spread complexity of the maximal entr…