Most Cited 2025 "microtransactions" Papers

DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning

Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.

Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability

Chen Wei, Chi Zhang, Jiachen Zou et al.

The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret

Lukas Fluri, Leon Lang, Alessandro Abate et al.

Regret-Free Reinforcement Learning for Temporal Logic Specifications

R Majumdar, Mahmoud Salamati, Sadegh Soudjani

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation

Chang Liu, Yixin Wang, Moontae Lee

ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals

Yuanchao Xu, Kaidi Shao, Nikos Logothetis et al.

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

Parshin Shojaee, Ngoc Hieu Nguyen, Kazem Meidani et al.

A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations

Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.

Retrieval-Augmented Language Model for Knowledge-aware Protein Encoding

Zhang Jiasheng, Delvin Zhang, Shuang Liang et al.

Learning Latent Graph Structures and their Uncertainty

Alessandro Manenti, Daniele Zambon, Cesare Alippi

Locality Preserving Markovian Transition for Instance Retrieval

Jifei Luo, Wenzheng Wu, Hantao Yao et al.

Adapting Precomputed Features for Efficient Graph Condensation

Yuan Li, Jun Hu, Zemin Liu et al.

TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization

Songtao Lu

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

One-Step Generalization Ratio Guided Optimization for Domain Generalization

Sumin Cho, Dongwon Kim, Kwangsu Kim

Learning to Route LLMs with Confidence Tokens

Yu-Neng Chuang, Prathusha Sarma, Parikshit Gopalan et al.

Trusted Multi-View Classification with Expert Knowledge Constraints

Xinyan Liang, Shijie Wang, Yuhua Qian et al.

Fast Video Generation with Sliding Tile Attention

Peiyuan Zhang, Yongqi Chen, Runlong Su et al.

Sleeping Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

UnHiPPO: Uncertainty-aware Initialization for State Space Models

Marten Lienen, Abdullah Saydemir, Stephan Günnemann

Preference learning made easy: Everything should be understood through win rate

Lily Zhang, Rajesh Ranganath

Super Deep Contrastive Information Bottleneck for Multi-modal Clustering

Zhengzheng Lou, Ke Zhang, Yucong Wu et al.

Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks

Liyuan Liang, Xinyi Chen, Gan Luo et al.

Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order Optimization

Hiroshi Sawada, Kazuo Aoyama, Yuya Hikima

LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification

Hang Gao, Huang Wenxuan, Fengge Wu et al.

Self-Consuming Generative Models with Adversarially Curated Data

Xiukun Wei, Xueru Zhang

Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold

Yilong Song, Peijin Li, Bin Gao et al.

Improving Out-of-Distribution Detection via Dynamic Covariance Calibration

Kaiyu Guo, Zijian Wang, Tan Pan et al.

OmniArch: Building Foundation Model for Scientific Computing

Tianyu Chen, Haoyi Zhou, Ying Li et al.

ESPFormer: Doubly-Stochastic Attention with Expected Sliced Transport Plans

Ashkan Shahbazi, Elaheh Akbari, Darian Salehi et al.

ConText: Driving In-context Learning for Text Removal and Segmentation

Fei Zhang, Pei Zhang, Baosong Yang et al.

Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures

Yingzhao Jian, Yue Zhang, Ying Wei et al.

Online Linear Classification with Massart Noise

Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.

Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detection

Anirudh Sundara Rajan, Yong Jae Lee

Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization

Ziyu Gong, Jim Lim, David I. Inouye

PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis

Sunghwan Hong, Jaewoo Jung, Heeseong Shin et al.

AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism

Zhepei Wei, Wei-Lin Chen, Xinyu Zhu et al.

InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective

Yuanhong Zhang, Muyao Yuan, Weizhan Zhang et al.

Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge

Hanglei Hu, Yingying Guo, Zhikang Chen et al.

Learning the Electronic Hamiltonian of Large Atomic Structures

Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas et al.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows

Gabriele Visentin, Patrick Cheridito

Interpreting the Repeated Token Phenomenon in Large Language Models

Itay Yona, Ilia Shumailov, Jamie Hayes et al.

Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series

Zachary Brown, David Carlson

Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling

Shuqi Lu, Xiaohong Ji, Bohang Zhang et al.

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks

Jeongmo Kim, Yisak Park, Minung Kim et al.

Diffusion Counterfactual Generation with Semantic Abduction

Rajat Rasal, Avinash Kori, Fabio De Sousa Ribeiro et al.

Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation

Guanglong Sun, Hongwei Yan, Liyuan Wang et al.

Learning Safe Control via On-the-Fly Bandit Exploration

Alexandre Capone, Ryan Cosner, Aaron Ames et al.

Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG

Wenbin Wang, Yongcheng Jing, Liang Ding et al.

A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations

Junwei Su, Chuan Wu

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning

Zihang Liu, Tianyu Pang, Oleg Balabanov et al.

K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes

Hideaki Kim, Tomoharu Iwata, Akinori Fujino

Large Continual Instruction Assistant

Jingyang Qiao, zhizhong zhang, Xin Tan et al.

When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration

Suorong Yang, Peng Ye, Furao Shen et al.

Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics

Hongbin Pei, Jingxin Hai, Yu Li et al.

Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling

Xinxing Shi, Xiaoyu Jiang, Mauricio Álvarez

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.

Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence

Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi et al.

Weakly-Supervised Contrastive Learning for Imprecise Class Labels

Zi-Hao Zhou, Jun-Jie Wang, Tong Wei et al.

Maintaining Proportional Committees with Dynamic Candidate Sets

Chris Dong, Jannik Peters

Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits

Jinzhao Li, Nan Jiang, Yexiang Xue

Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random Inputs

Andrey Kofnov, Daniel Kapla, Ezio Bartocci et al.

Reward Translation via Reward Machine in Semi-Alignable MDPs

Yun Hua, Haosheng Chen, Wenhao Li et al.

Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation

He Li, Haoang Chi, Mingyu Liu et al.

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen et al.

Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks

Sungwon Kim, Namkyeong Lee, Yunyoung Doh et al.

Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts

Haoyang Li, Xin Wang, Xueling Zhu et al.

TUMTraf VideoQA: Dataset and Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes

Xingcheng Zhou, Konstantinos Larintzakis, Hao Guo et al.

Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries

Junhyuck Kim, Jongho Park, Jaewoong Cho et al.

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales

Ju-Seung Byun, Andrew Perrault

Catching Two Birds with One Stone: Reward Shaping with Dual Random Networks for Balancing Exploration and Exploitation

Haozhe Ma, Fangling Li, Jing Lim et al.

PASS: Private Attributes Protection with Stochastic Data Substitution

Yizhuo Chen, Chun-Fu (Richard) Chen, Hsiang Hsu et al.

Settling the Maximin Share Fairness for Scheduling among Groups of Machines

Bo Li, Fangxiao WANG, Xing Shiji

ETTA: Elucidating the Design Space of Text-to-Audio Models

Sang-gil Lee, Zhifeng Kong, ARUSHI GOEL et al.

Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks

Xianliang Xu, Ye Li, Zhongyi Huang

Flow-field inference from neural data using deep recurrent networks

Timothy Doyeon Kim, Thomas Luo, Tankut Can et al.

Do Vision-Language Models Really Understand Visual Language?

Yifan Hou, Buse Giledereli, Yilei Tu et al.

Concept-Based Unsupervised Domain Adaptation

Xinyue Xu, Yueying Hu, Hui Tang et al.

On the Out-of-Distribution Generalization of Self-Supervised Learning

Wenwen Qiang, Jingyao Wang, Zeen Song et al.

Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection

Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.

Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime

Diyuan Wu, Marco Mondelli

Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning

Brett Barkley, David Fridovich-Keil

Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments

Qianglin Wen, Chengchun Shi, Ying Yang et al.

Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints

Ruichuan Huang, Jiawei Zhang, Ahmet Alacaoglu

Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models

Taj Jones-McCormick, Aukosh Jagannath, Subhabrata Sen

Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation

Juncheol Shin, Minsang Seok, Seonggon Kim et al.

Training Dynamics of In-Context Learning in Linear Attention

Yedi Zhang, Aaditya Singh, Peter Latham et al.

STAIR: Improving Safety Alignment with Introspective Reasoning

Yichi Zhang, Siyuan Zhang, Yao Huang et al.

AtlasD: Automatic Local Symmetry Discovery

Manu Bhat, Jonghyun Park, Jianke Yang et al.

Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning

Motoki Omura, Kazuki Ota, Takayuki Osa et al.

Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors

Shuangpeng Han, Mengmi Zhang

Adversarial Reasoning at Jailbreaking Time

Mahdi Sabbaghi, Paul Kassianik, George Pappas et al.

Calibrating Video Watch-time Predictions with Credible Prototype Alignment

Chao, Shisong Tang, Fan Li et al.

$\infty$-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation

Saúl Santos, António Farinhas, Daniel McNamee et al.

Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks

Jincheng Huang, Yujie Mo, Xiaoshuang Shi et al.

Non-stationary Diffusion For Probabilistic Time Series Forecasting

Weiwei Ye, Zhuopeng Xu, Ning Gui

ROME is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck

Zheng Zhou, Wenquan Feng, Qiaosheng Zhang et al.

Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale

Fan Zhou, Zengzhi Wang, Qian Liu et al.

Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors

Matei Gabriel Cosa, Marek Elias

Compositional Risk Minimization

Divyat Mahajan, Mohammad Pezeshki, Charles Arnal et al.

The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models

Zichao Li, Xueru Wen, Jie Lou et al.

Efficiently Access Diffusion Fisher: Within the Outer Product Span Space

Fangyikang Wang, Hubery Yin, Shaobin Zhuang et al.

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training

Fabian Schaipp, Alexander Hägele, Adrien Taylor et al.

Automated Red Teaming with GOAT: the Generative Offensive Agent Tester

Maya Pavlova, Erik Brinkman, Krithika Iyer et al.

The Price of Linear Time: Error Analysis of Structured Kernel Interpolation

Alexander Moreno, Justin Xiao, Jonathan Mei

Language Models May Verbatim Complete Text They Were Not Explicitly Trained On

Ken Ziyu Liu, Christopher A. Choquette Choo, Matthew Jagielski et al.

InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference

Tianyu Cui, Song-Jun Xu, Artem Moskalev et al.

A Machine Learning Approach to Duality in Statistical Physics

Prateek Gupta, Andrea Ferrari, Nabil Iqbal

Polynomial-Time Approximability of Constrained Reinforcement Learning

Jeremy McMahan

Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence

zhaowei chen, Borui Zhao, Yuchen Ge et al.

Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective

Qingchuan Ma, Yuhang Wu, Xiawu Zheng et al.

No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks

Attila Szász, Balázs Bánhelyi, Mark Jelasity

ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification

Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim et al.

A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs

Kihyuk Hong, Ambuj Tewari

Large Language Models are Demonstration Pre-Selectors for Themselves

Jiarui Jin, Yuwei Wu, Haoxuan Li et al.

WAVE: Weighted Autoregressive Varying Gate for Time Series Forecasting

Jiecheng Lu, Xu Han, Yan Sun et al.

Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing

Yuan Xin, Dingfan Chen, Michael Backes et al.

Large Language-Geometry Model: When LLM meets Equivariance

Zongzhao Li, Jiacheng Cen, Bing Su et al.

Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling

Jinghan Li, Zhicheng Sun, Yadong Mu

AdaSplash: Adaptive Sparse Flash Attention

Nuno Gonçalves, Marcos V. Treviso, Andre Martins

Open Materials Generation with Stochastic Interpolants

Philipp Höllmer, Thomas Egg, Maya Martirossyan et al.

µnit Scaling: Simple and Scalable FP8 LLM Training

Saaketh Narayan, Abhay Gupta, Mansheej Paul et al.

AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment

Yuqin Cao, Xiongkuo Min, Yixuan Gao et al.

GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance

Jinuk Kim, Marwa El Halabi, Wonpyo Park et al.

HyperIV: Real-time Implied Volatility Smoothing

Yongxin Yang, Wenqi Chen, Chao Shu et al.

Attributes Shape the Embedding Space of Face Recognition Models

Pierrick Leroy, Antonio Mastropietro, Marco Nurisso et al.

Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion

KAIJUN LIU, Sijie Ruan, Liang Zhang et al.

Optimal Auction Design in the Joint Advertising

Yang Li, Yuchao Ma, Qi Qi

LASER: Attention with Exponential Transformation

Sai Surya Duvvuri, Inderjit Dhillon

Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World

Joshua Kazdan, Rylan Schaeffer, Apratim Dey et al.

Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting

Jiecheng Lu, Shihao Yang

Textual Unlearning Gives a False Sense of Unlearning

Jiacheng Du, Zhibo Wang, Jie Zhang et al.

One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs

Yinghui Li, Jiayi Kuang, Haojing Huang et al.

Probing Visual Language Priors in VLMs

Tiange Luo, Ang Cao, Gunhee Lee et al.

Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes

Jie Liu, Pan Zhou, Zehao Xiao et al.

HPS: Hard Preference Sampling for Human Preference Alignment

Xiandong Zou, Wanyu LIN, Yuchen Li et al.

Control and Realism: Best of Both Worlds in Layout-to-Image without Training

Bonan Li, Yinhan Hu, Songhua Liu et al.

The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport

Chenrui Wang, Yixuan Qiu

SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding

Woohyeon Park, Woojin Kim, Jaeik Kim et al.

AMPO: Active Multi Preference Optimization for Self-play Preference Selection

Taneesh Gupta, Rahul Madhavan, Xuchao Zhang et al.

Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation

Tianyi Zhang, Junda Su, Aditya Desai et al.

Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism

Aviv Bick, Eric Xing, Albert Gu

Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models

Yuan Li, Zhengzhong Liu, Eric Xing

Guided Structural Inference: Leveraging Priors with Soft Gating Mechanisms

Aoran Wang, Xinnan Dai, Jun Pang

Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity

Quan Nguyen, Nishant Mehta, Cristóbal Guzmán

Knowledge Retention in Continual Model-Based Reinforcement Learning

Haotian Fu, Yixiang Sun, Michael L. Littman et al.

Ranked from Within: Ranking Large Multimodal Models Without Labels

Weijie Tu, Weijian Deng, Dylan Campbell et al.

Improved Approximations for Hard Graph Problems using Predictions

Anders Aamand, Justin Chen, Siddharth Gollapudi et al.

Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition

Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures

Jie Gao, Rajesh Jayaram, Benedikt Kolbe et al.

Adversarial Combinatorial Semi-bandits with Graph Feedback

Yuxiao Wen

RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts

Tuan Truong, Chau Nguyen, Huy Nguyen et al.

Tracking Most Significant Shifts in Infinite-Armed Bandits

Joe Suk, Jung-hun Kim

When to Forget? Complexity Trade-offs in Machine Unlearning

Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia et al.

Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language Models

Rei Higuchi, Taiji Suzuki

Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning

Ryotaro Kawata, Kohsei Matsutani, Yuri Kinoshita et al.

Provable In-Context Vector Arithmetic via Retrieving Task Concepts

Dake Bu, Wei Huang, Andi Han et al.

On the Role of Label Noise in the Feature Learning Process

Andi Han, Wei Huang, Zhanpeng Zhou et al.

EgoPrivacy: What Your First-Person Camera Says About You?

Yijiang Li, Genpei Zhang, Jiacheng Cheng et al.

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

Shaobin Zhuang, Yiwei Guo, Yanbo Ding et al.

Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme

Ruofeng Yang, Bo Jiang, Cheng Chen et al.

Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu et al.

PipeOffload: Improving Scalability of Pipeline Parallelism with Memory Optimization

Xinyi Wan, Penghui Qi, Guangxing Huang et al.

LEMoN: Label Error Detection using Multimodal Neighbors

Haoran Zhang, Aparna Balagopalan, Nassim Oufattole et al.

M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation

Tao Zhang, Zhenhai Liu, Feipeng Qi et al.

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control

Peiyan Hu, Xiaowei Qian, Wenhao Deng et al.

Near-optimal Sketchy Natural Gradients for Physics-Informed Neural Networks

Maricela Best Mckay, Avleen Kaur, Chen Greif et al.

Defending LVLMs Against Vision Attacks Through Partial-Perception Supervision

Qi Zhou, Dongxia Wang, Tianlin Li et al.

Neural Event-Triggered Control with Optimal Scheduling

Luan Yang, Jingdong Zhang, Qunxi Zhu et al.

Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift

Nguyen Nhat Minh To, Paul Wilson, Viet Nguyen et al.

Towards Efficient Online Tuning of VLM Agents via Counterfactual Soft Reinforcement Learning

Lang Feng, Weihao Tan, Zhiyi Lyu et al.

GraphGPT: Generative Pre-trained Graph Eulerian Transformer

Qifang Zhao, Weidong Ren, Tianyu Li et al.

Generalization Analysis for Controllable Learning

Yi-Fan Zhang, Xiao Zhang, Min-Ling Zhang

Tight and Fast Bounds for Multi-Label Learning

Yi-Fan Zhang, Min-Ling Zhang

Spherical Rotation Dimension Reduction with Geometric Loss Functions

Hengrui Luo, Jeremy E. Purvis, Didong Li

Semi-Supervised Blind Quality Assessment with Confidence-quantifiable Pseudo-label Learning for Authentic Images

Yan Zhong, Chenxi Yang, Suyuan Zhao et al.

COKE: Core Kernel for More Efficient Approximation of Kernel Weights in Multiple Kernel Clustering

Weixuan Liang, Xinwang Liu, KE LIANG et al.

Improving the Scaling Laws of Synthetic Data with Deliberate Practice

Reyhane Askari Hemmat, Mohammad Pezeshki, Elvis Dohmatob et al.

Socialized Coevolution: Advancing a Better World through Cross-Task Collaboration

Xinjie Yao, Yu Wang, Pengfei Zhu et al.

Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction

Yadong Sun, Xiaofeng Cao, Ivor Tsang et al.

MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES

Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk et al.

Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg

Like Jian, Dong Liu

Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation

Yihao Yang, Wenke Huang, Guancheng Wan et al.

Enhancing Graph Invariant Learning from a Negative Inference Perspective

Kuo Yang, Zhengyang Zhou, Qihe Huang et al.

OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?

Liangze Jiang, Damien Teney

Complete-Tree Space Favors Data-Efficient Link Prediction

Chi Gao, Lukai Li, Yancheng Zhou et al.

DLP: Dynamic Layerwise Pruning in Large Language Models

Yuli Chen, Bo Cheng, Jiale Han et al.

ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning

Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik et al.

Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation

CHUANQI CHENG, Jian Guan, Wei Wu et al.

E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel Time

Adam Breuer

Learning to Reuse Policies in State Evolvable Environments

Ziqian Zhang, Bohan Yang, Lihe Li et al.

Kona: An Efficient Privacy-Preservation Framework for KNN Classification by Communication Optimization

Guopeng Lin, Ruisheng Zhou, Shuyu Chen et al.

La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation

Kai Liu, Bowen Xu, Shaoyu Wu et al.

Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data

Zhe Zhao, HaiBin Wen, Pengkun Wang et al.

Understanding High-Dimensional Bayesian Optimization

Leonard Papenmeier, Matthias Poloczek, Luigi Nardi

Learning Configurations for Data-Driven Multi-Objective Optimization

Zhiyang Chen, Hailong Yao, Xia Yin

Mutual Learning for SAM Adaptation: A Dual Collaborative Network Framework for Source-Free Domain Transfer

Yabo Liu, Waikeung Wong, Chengliang Liu et al.

End-to-End Learning Framework for Solving Non-Markovian Optimal Control

Xiaole Zhang, Peiyu Zhang, Xiongye Xiao et al.

Iterative Vectors: In-Context Gradient Steering without Backpropagation

Yiting Liu, Zhi-Hong Deng

Doubly Robust Fusion of Many Treatments for Policy Learning

Ke Zhu, Jianing Chu, Ilya Lipkovich et al.