Most Cited 2025 "ventral stream selectivity" Papers
22,274 papers found • Page 86 of 112
Conference
Robust ML Auditing using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas et al.
Exogenous Isomorphism for Counterfactual Identifiability
Yikang Chen, Dehui du
Optimizing Adaptive Attacks against Watermarks for Language Models
Abdulrahman Diaa, Toluwani Aremu, Nils Lukas
FRUGAL: Memory-Efficient Optimization by Reducing State Overhead for Scalable Training
Filipp Zmushko, Aleksandr Beznosikov, Martin Takac et al.
Generative Data Mining with Longtail-Guided Diffusion
David Hayden, Mao Ye, Timur Garipov et al.
CoSER: Coordinating LLM-Based Persona Simulation of Established Roles
Xintao Wang, Heng Wang, Yifei Zhang et al.
Multi-Session Budget Optimization for Forward Auction-based Federated Learning
Xiaoli Tang, Han Yu, Zengxiang Li et al.
Wait-Less Offline Tuning and Re-solving for Online Decision Making
Jingruo Sun, Wenzhi Gao, Ellen Vitercik et al.
DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton et al.
Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
Hongyi Zhou, Josiah Hanna, Jin Zhu et al.
MetricEmbedding: Accelerate Metric Nearness by Tropical Inner Product
Muyang Cao, Jiajun Yu, Xin Du et al.
Strategic A/B testing via Maximum Probability-driven Two-armed Bandit
Yu Zhang, Shanshan Zhao, Bokui Wan et al.
Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination
Zhihan Zhu, Yanhao Zhang, Yong Xia
The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)
Zihao Wang, Yibo Jiang, Jiahao Yu et al.
Playmate: Flexible Control of Portrait Animation via 3D-Implicit Space Guided Diffusion
Xingpei Ma, Jiaran Cai, Yuansheng Guan et al.
LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs – No Silver Bullet for LC or RAG Routing
Kuan Li, Liwen Zhang, Yong Jiang et al.
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training
Chao Ma, Wenbo Gong, Meyer Scetbon et al.
More Than Meets the Eye: Enhancing Multi-Object Tracking Even with Prolonged Occlusions
Bishoy Galoaa, Somaieh Amraee, Sarah Ostadabbas
Generalization Performance of Ensemble Clustering: From Theory to Algorithm
Xu Zhang, Haoye Qiu, Weixuan Liang et al.
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
Łukasz Struski, Michal Bednarczyk, Igor Podolak et al.
Near-Optimal Sample Complexity for MDPs via Anchoring
Jongmin Lee, Mario Bravo, Roberto Cominetti
Rethinking Aleatoric and Epistemic Uncertainty
Freddie Bickford Smith, Jannik Kossen, Eleanor Trollope et al.
Sample Complexity of Branch-length Estimation by Maximum Likelihood
David Clancy, Hanbaek Lyu, Sebastien Roch
Comparing Comparisons: Informative and Easy Human Feedback with Distinguishability Queries
Xuening Feng, Zhaohui Jiang, Timo Kaufmann et al.
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
Ruinan Jin, Xiao Li, Yaoliang Yu et al.
Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune et al.
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning
Gaoyue Zhou, Hengkai Pan, Yann LeCun et al.
Robust Automatic Modulation Classification with Fuzzy Regularization
Xinyan Liang, Ruijie Sang, Yuhua Qian et al.
Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification
Kapilan Balagopalan, Tuan Nguyen, Yao Zhao et al.
Efficient Robotic Policy Learning via Latent Space Backward Planning
Dongxiu Liu, Haoyi Niu, Zhihao Wang et al.
Measuring Diversity in Synthetic Datasets
Yuchang Zhu, Huizhe Zhang, Bingzhe Wu et al.
Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
Agent-as-a-Judge: Evaluate Agents with Agents
Mingchen Zhuge, Changsheng Zhao, Dylan Ashley et al.
RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
Yushuai Li, Hengyu Liu, Torben Pedersen et al.
Metadata Conditioning Accelerates Language Model Pre-training
Tianyu Gao, Alexander Wettig, Luxi He et al.
Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving
Ankit Bhardwaj, Amar Phanishayee, Deepak Narayanan et al.
Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Perceptually Constrained Precipitation Nowcasting Model
Wenzhi Feng, Xutao Li, Zhe Wu et al.
Differentially Private Federated $k$-Means Clustering with Server-Side Data
Jonathan Scott, Christoph Lampert, David Saulpic
QUTE: Quantifying Uncertainty in TinyML models with Early-exit-assisted ensembles for model-monitoring
Nikhil Pratap Ghanathe, Steve Wilton
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
Bingshan Hu, Zhiming Huang, Tianyue Zhang et al.
AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
Junkang Wu, xue wang, Zhengyi Yang et al.
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, J. Kim
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng, Wen Li, Zhaoqiang Liu
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Yongxian Wei, Anke Tang, Li Shen et al.
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu et al.
Benchmarking Quantum Reinforcement Learning
Nico Meyer, Christian Ufrecht, George Yammine et al.
Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model
Yuzhong Hong, Hanshan Zhang, Junwei Bao et al.
Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen et al.
Is Complex Query Answering Really Complex?
Cosimo Gregucci, Bo Xiong, Daniel Hernández et al.
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer et al.
On Path to Multimodal Generalist: General-Level and General-Bench
Hao Fei, Yuan Zhou, Juncheng Li et al.
Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi et al.
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Thibaud Southiratn, Bonil Koo, Yijingxiu Lu et al.
Improved Online Confidence Bounds for Multinomial Logistic Bandits
Joongkyu Lee, Min-hwan Oh
Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing
Kento Nishi, Rahul Ramesh, Maya Okawa et al.
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna Ballard, Mohan Zhang et al.
Variance as a Catalyst: Efficient and Transferable Semantic Erasure Adversarial Attack for Customized Diffusion Models
Jiachen Yang, Yusong Wang, Yanmei Fang et al.
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng et al.
Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
Shuqing Luo, Pingzhi Li, Jie Peng et al.
Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback
Tal Lancewicki, Yishay Mansour
Stabilizing Sample Similarity in Representation via Mitigating Random Consistency
Jieting Wang, ZhangZelong Zhang, Feijiang Li et al.
On Explaining Equivariant Graph Networks via Improved Relevance Propagation
Hongyi Ling, Haiyang Yu, Zhimeng Jiang et al.
Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences
Yunhong Lu, Qichao Wang, Hengyuan Cao et al.
Adversaries Can Misuse Combinations of Safe Models
Erik Jones, Anca Dragan, Jacob Steinhardt
Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
Kulin Shah, Alkis Kalavasis, Adam Klivans et al.
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu et al.
WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales
Drew Prinster, Xing Han, Anqi Liu et al.
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
Yunyi Shen, Hao Sun, Jean-Francois Ton
Upcycling Text-to-Image Diffusion Models for Multi-Task Capabilities
Ruchika Chavhan, Abhinav Mehrotra, Malcolm Chadwick et al.
TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
Qihe Huang, Zhengyang Zhou, Kuo Yang et al.
GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
Ekaterina Filimoshina, Dmitry Shirokov
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
Xiaoyu Wu, Jiaru Zhang, Steven Wu
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell et al.
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh et al.
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
Vladimir Kostic, Karim Lounici, Hélène Halconruy et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
Huafeng Liu, Yiran Fu, Liping Jing et al.
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, Wieland Brendel et al.
Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence
Joseph Paillard, Angel REYERO LOBO, Vitaliy Kolodyazhniy et al.
Position: Language model developers should report train-test overlap
Andy Zhang, Kevin Klyman, Yifan Mai et al.
LEAPS: A discrete neural sampler via locally equivariant networks
Peter Holderrieth, Michael Albergo, Tommi Jaakkola
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu et al.
FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Gabriel Müller et al.
AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao et al.
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis et al.
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
Yassine Abbahaddou, Fragkiskos Malliaros, Johannes Lutzeyer et al.
Symmetry-Aware GFlowNets
Hohyun Kim, Seunggeun Lee, Min-hwan Oh
FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
Yingying Deng, Xiangyu He, Changwang Mei et al.
Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia et al.
Test-Time Canonicalization by Foundation Models for Robust Perception
Utkarsh Singhal, Ryan Feng, Stella Yu et al.
Trustworthy Machine Learning through Data-Specific Indistinguishability
Hanshen Xiao, Zhen Yang, Edward Suh
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications
Ibrahim Fayad, Max Zimmer, Martin Schwartz et al.
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach
Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar et al.
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre et al.
ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
Guanghui Wang, Zhiyong Yang, Zitai Wang et al.
Preference Optimization for Combinatorial Optimization Problems
Mingjun Pan, Guanquan Lin, You-Wei Luo et al.
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin et al.
Improving Model Alignment Through Collective Intelligence of Open-Source Models
Junlin Wang, Roy Xie, Shang Zhu et al.
GradPS: Resolving Futile Neurons in Parameter Sharing Network for Multi-Agent Reinforcement Learning
Haoyuan Qin, Zhengzhu Liu, Chenxing Lin et al.
Do We Really Need Message Passing in Brain Network Modeling?
Liang Yang, Yuwei Liu, Jiaming Zhuo et al.
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
Towards Memorization Estimation: Fast, Formal and Free
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
How Far Is Video Generation from World Model: A Physical Law Perspective
Bingyi Kang, Yang Yue, Rui Lu et al.
SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution
Wenwen He, Wenke Huang, Bin Yang et al.
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei et al.
Expected Variational Inequalities
Brian Zhang, Ioannis Anagnostides, Emanuel Tewolde et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant et al.
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement
Yuheng Jing, Kai Li, Bingyun Liu et al.
On the Power of Context-Enhanced Learning in LLMs
Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe et al.
The Underlying Universal Statistical Structure of Natural Datasets
Noam Levi, Yaron Oz
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization
Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan et al.
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
Chengmei Niu, Zhenyu Liao, Zenan Ling et al.
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.
When and How Does CLIP Enable Domain and Compositional Generalization?
Elias Kempf, Simon Schrodi, Max Argus et al.
IT$^3$: Idempotent Test-Time Training
Nikita Durasov, Assaf Shocher, Doruk Oner et al.
Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
Tom Jacobs, Chao Zhou, Rebekka Burkholz
MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
Zihan Chen, Song Wang, Zhen Tan et al.
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, jiangtao wen, Yuxing Han
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models
Xingyu Chen, Jiahao Xu, Tian Liang et al.
Towards Better-than-2 Approximation for Constrained Correlation Clustering
Andreas Kalavas, Evangelos Kipouridis, Nithin Varma
Scaling Sparse Feature Circuits For Studying In-Context Learning
Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.
Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang et al.
Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization
Zelai Xu, Wanjun Gu, Chao Yu et al.
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models
Changyi He, Yifu Ding, Jinyang Guo et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
MissScore: High-Order Score Estimation in the Presence of Missing Data
Wenqin Liu, Haoze Hou, Erdun Gao et al.
MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
Jeffrey A. Chan-Santiago, praveen tirupattur, Gaurav Kumar Nayak et al.
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier, Sourav Medya
MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
Yang Luo, Zangwei Zheng, Ziheng Qin et al.
Online Laplacian-Based Representation Learning in Reinforcement Learning
Maheed Ahmed, Jayanth Bhargav, Mahsa Ghasemi
RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
Ching-Hua Lee, Chouchang Yang, Jaejin Cho et al.
Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
Hengquan Guo, Lingkai Zu, Xin Liu
Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
Ya-Chi Chu, Wenzhi Gao, Yinyu Ye et al.
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh
Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model
Rachel Cummings, Alessandro Epasto, Jieming Mao et al.
Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds
Emanuele Troiani, Hugo Cui, Yatin Dandi et al.
One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework
Feiran Li, Qianqian Xu, Shilong Bao et al.
Algorithms with Calibrated Machine Learning Predictions
Judy Hanwen Shen, Ellen Vitercik, Anders Wikum
Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
Manwen Liao, Yan Zhu, Weitian Zhang et al.
Hypothesis Testing for Generalized Thurstone Models
Anuran Makur, Japneet Singh
Multi-Objective Causal Bayesian Optimization
Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.
An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang et al.
Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
Tomer Meir, Uri Shalit, Malka Gorfine
Staged and Physics-Grounded Learning Framework with Hyperintensity Prior for Pre-Contrast MRI Synthesis
Dayang Wang, Srivathsa Pasumarthi Venkata, Ajit Shankaranarayanan et al.
Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang et al.
From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning
Jinyu Wang, Jingjing Fu, Rui Wang et al.
SSHR: More Secure Generative Steganography with High-Quality Revealed Secret Images
Jiannian Wang, Yao Lu, Guangming Lu
FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
Zheng Fang, Lichuan Xiang, Xu Cai et al.
Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization
Kyurae Kim, Zuheng Xu, Jacob Gardner et al.
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
Conformity Score Averaging for Classification
Rui Luo, Zhixin Zhou
Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints
Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.
GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation
Mengzhu Wang, houcheng su, Jiao Li et al.
Revisiting the Predictability of Performative, Social Events
Juan Perdomo
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan et al.
Provable Zero-Shot Generalization in Offline Reinforcement Learning
Zhiyong Wang, Chen Yang, John C. S. Lui et al.
Nonconvex Theory of $M$-estimators with Decomposable Regularizers
Weiwei Liu
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey et al.
Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
Chao Yang, Shuting Cui, Yang Yang et al.
Star Attention: Efficient LLM Inference over Long Sequences
Shantanu Acharya, Fei Jia, Boris Ginsburg
GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
Yuhang Li, Ruokai Yin, Donghyun Lee et al.
Hidden No More: Attacking and Defending Private Third-Party LLM Inference
Rahul Thomas, Louai Zahran, Erica Choi et al.
Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
Shira Vansover-Hager, Tomer Koren, Roi Livni
KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Haihong E, Yikai Guo et al.
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.
Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View Learning
Xue Zhao, Qinying Gu, Xinbing Wang et al.
Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
Haoqi Wu, Wei Dai, Wang Li et al.
Zero-Shot Generalization of GNNs over Distinct Attribute Domains
Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua et al.
PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
Chenyu Li, Oscar Michel, Xichen Pan et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium
Yi Xie, Zhanke Zhou, Chentao Cao et al.
Residual Matrix Transformers: Scaling the Size of the Residual Stream
Brian Mak, Jeffrey Flanigan
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich et al.
Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems
Shaokun Zhang, Ming Yin, Jieyu Zhang et al.
ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
Alec Helbling, Tuna Han Salih Meral, Benjamin Hoover et al.
Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks
Rui Xue, Tong Zhao, Neil Shah et al.
An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data
Nikita Lagrange, Herve Isambert
SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification
Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
Customizing the Inductive Biases of Softmax Attention using Structured Matrices
Yilun Kuang, Noah Amsel, Sanae Lotfi et al.
RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
Payman Behnam, Yaosheng Fu, Ritchie Zhao et al.
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai, Pin-Han Huang, Bo-Han Kung et al.
Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur et al.