Most Cited NEURIPS "shap values" Papers
5,858 papers found • Page 12 of 30
Conference
Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies
Felix Chalumeau, Daniel Rajaonarivonivelomanantsoa, Ruan John de Kock et al.
DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
Antonio Guillen-Perez, Avisek Naug, Vineet Gundecha et al.
Bayes optimal learning of attention-indexed models
Fabrizio Boncoraglio, Emanuele Troiani, Vittorio Erba et al.
StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training
Ziming Liu, Shaoyu Wang, Shenggan Cheng et al.
A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation
Yiwen Tu, Pingbang Hu, Jiaqi Ma
LooGLE v2: Are LLMs Ready for Real World Long Dependency Challenges?
Ziyuan He, Yuxuan Wang, Jiaqi Li et al.
Rethinking Nighttime Image Deraining via Learnable Color Space Transformation
Qiyuan Guan, Xiang Chen, Guiyue Jin et al.
msf-CNN: Patch-based Multi-Stage Fusion with Convolutional Neural Networks for TinyML
Zhaolan Huang, Emmanuel Baccelli
Model-Based Policy Adaptation for Closed-Loop End-to-end Autonomous Driving
Haohong Lin, Yunzhi Zhang, Wenhao Ding et al.
Generalized Contrastive Learning for Universal Multimodal Retrieval
Jungsoo Lee, Janghoon Cho, Hyojin Park et al.
Convex Approximation of Two-Layer ReLU Networks for Hidden State Differential Privacy
Rob Romijnders, Antti Koskela
Unifying Proportional Fairness in Centroid and Non-Centroid Clustering
Benjamin Cookson, Nisarg Shah, Ziqi Yu
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
SRHand: Super-Resolving Hand Images and 3D Shapes via View/Pose-aware Neural Image Representations and Explicit Meshes
Minje Kim, Tae-Kyun Kim
The Underappreciated Power of Vision Models for Graph Structural Understanding
Xinjian Zhao, Wei Pang, Zhongkai Xue et al.
Learning Temporal 3D Semantic Scene Completion via Optical Flow Guidance
meng wang, Fan Wu, Ruihui Li et al.
Path Gradients after Flow Matching
Lorenz Vaitl, Leon Klein
VITRIX-CLIPIN: Enhancing Fine-Grained Visual Understanding in CLIP via Instruction-Editing Data and Long Captions
Ziteng Wang, Siqi Yang, Limeng Qiao et al.
Gradient Variance Reveals Failure Modes in Flow-Based Generative Models
Teodora Reu, Sixtine Dromigny, Michael Bronstein et al.
Measuring and Guiding Monosemanticity
Ruben Härle, Felix Friedrich, Manuel Brack et al.
Learning to Insert for Constructive Neural Vehicle Routing Solver
Fu Luo, Xi Lin, Mengyuan Zhong et al.
Semi-off-Policy Reinforcement Learning for Vision-Language Slow-Thinking Reasoning
Junhao Shen, Haiteng Zhao, Yuzhe Gu et al.
MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series
Payal Mohapatra, Yueyuan Sui, Akash Pandey et al.
Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
Alex Fang, Hadi Pouransari, Matt Jordan et al.
Riemannian Consistency Model
Chaoran Cheng, Yusong Wang, Yuxin Chen et al.
Learning Dense Hand Contact Estimation from Imbalanced Data
Daniel Jung, Kyoung Mu Lee
GUARD: Constructing Realistic Two-Player Matrix and Security Games for Benchmarking Game-Theoretic Algorithms
Noah Krever, Jakub Cerny, Moise Blanchard et al.
OmniGaze: Reward-inspired Generalizable Gaze Estimation in the Wild
Hongyu Qu, Jianan Wei, Xiangbo Shu et al.
Multivariate Dynamic Mediation Analysis under a Reinforcement Learning Framework
Lan Luo, Chengchun Shi, Jitao Wang et al.
scMRDR: A scalable and flexible framework for unpaired single-cell multi-omics data integration
Jianle Sun, Chaoqi Liang, Ran Wei et al.
Spark Transformer: Reactivating Sparsity in Transformer FFN and Attention
Chong You, Kan Wu, Zhipeng Jia et al.
Panoptic Captioning: An Equivalence Bridge for Image and Text
Kun-Yu Lin, Hongjun Wang, Weining Ren et al.
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
Jiani Liu, Zhiyuan Wang, Zeliang Zhang et al.
On the Hardness of Conditional Independence Testing In Practice
Zheng He, Roman Pogodin, Yazhe Li et al.
Max Entropy Moment Kalman Filter for Polynomial Systems with Arbitrary Noise
Sangli Teng, Harry Zhang, David Jin et al.
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
Zhining Liu, Zihao Li, Ze Yang et al.
QUT-DV25: A Dataset for Dynamic Analysis of Next-Gen Software Supply Chain Attacks
Sk Tanzir Mehedi, Raja Jurdak, Chadni Islam et al.
Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
Sebastian Kassing, Simon Weissmann, Leif Döring
STAR: A Benchmark for Astronomical Star Fields Super-Resolution
WU KUO-CHENG, Guohang Zhuang, Jinyang Huang et al.
The Generative Leap: Tight Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
Alex Damian, Jason Lee, Joan Bruna
Diffusion Generative Modeling on Lie Group Representations
Marco Bertolini, Tuan Le, Djork-Arné Clevert
Infinite-Width Limit of a Single Attention Layer: Analysis via Tensor Programs
Mana Sakai, Ryo Karakida, Masaaki Imaizumi
Distributional Autoencoders Know the Score
Andrej Leban
Reconstruct, Inpaint, Test-Time Finetune: Dynamic Novel-view Synthesis from Monocular Videos
Kaihua Chen, Tarasha Khurana, Deva Ramanan
Constructing an Optimal Behavior Basis for the Option Keyboard
Lucas N. Alegre, Ana Bazzan, Andre Barreto et al.
CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis
Florian Barthel, Wieland Morgenstern, Paul Hinzer et al.
Distributionally Robust Performative Optimization
Zhuangzhuang Jia, Yijie Wang, Roy Dong et al.
Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
Continual Knowledge Adaptation for Reinforcement Learning
Jinwu Hu, ZiHao Lian, Zhiquan Wen et al.
Exploiting Vocabulary Frequency Imbalance in Language Model Pre-training
Woojin Chung, Jeonghoon Kim
Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning
Till Freihaut, Luca Viano, Volkan Cevher et al.
Understanding the Evolution of the Neural Tangent Kernel at the Edge of Stability
Kaiqi Jiang, Jeremy Cohen, Yuanzhi Li
Imagined Autocurricula
Ahmet Hamdi Güzel, Matthew T Jackson, Jarek Liesen et al.
Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
Nathanael Jo, Ashia Wilson, Kathleen Creel et al.
From Black-box to Causal-box: Towards Building More Interpretable Models
Inwoo Hwang, Yushu Pan, Elias Bareinboim
Towards Large-Scale In-Context Reinforcement Learning by Meta-Training in Randomized Worlds
Fan Wang, Pengtao Shao, Yiming Zhang et al.
Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
Shlomi Hod, Lucas Rosenblatt, Julia Stoyanovich
Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization
Noémie Bergues, Arthur Carré, Paul Join-Lambert et al.
PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
Yanlong Chen, Mattia Orlandi, Pierangelo Rapa et al.
Pairwise Calibrated Rewards for Pluralistic Alignment
Daniel Halpern, Evi Micha, Ariel Procaccia et al.
Limitations of Normalization in Attention
Timur Mudarisov, Mikhail Burtsev, Tatiana Petrova et al.
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo et al.
Dense Backpropagation Improves Training for Sparse Mixture-of-Experts
Ashwinee Panda, Vatsal Baherwani, Zain Sarwar et al.
DuoGPT: Training-free Dual Sparsity through Activation-aware Pruning in LLMs
Ruokai Yin, Yuhang Li, Donghyun Lee et al.
SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer
Yarden As, Chengrui (Ray) Qu, Benjamin Unger et al.
Dynamic Regret Reduces to Kernelized Static Regret
Andrew Jacobsen, Alessandro Rudi, Francesco Orabona et al.
Statistical Inference under Performativity
Xiang Li, Yunai Li, Huiying Zhong et al.
GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
Simin Fan, Maria Ios Glarou, Martin Jaggi
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
Longwei Wang, Ifrat Ikhtear Uddin, Prof. KC Santosh (PhD) et al.
ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search
Zeyu Shen, Basileal Imana, Tong Wu et al.
Connecting Neural Models Latent Geometries with Relative Geodesic Representations
Hanlin Yu, Berfin Inal, Georgios Arvanitidis et al.
Rethinking Optimal Verification Granularity for Compute-Efficient Test-Time Scaling
Hao Chen, Guanxi Lu, Yasuyuki Okoshi et al.
V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel Simulation
Hanyue Lou, Jinxiu Liang, Minggui Teng et al.
PhySense: Sensor Placement Optimization for Accurate Physics Sensing
Yuezhou Ma, Haixu Wu, Hang Zhou et al.
Decoupling Contrastive Decoding: Robust Hallucination Mitigation in Multimodal Large Language Models
Wei Chen, Xin Yan, Bin Wen et al.
Rethinking Residual Distribution in Locate-then-Edit Model Editing
Xiaopeng Li, Shangwen Wang, Shasha Li et al.
System-Embedded Diffusion Bridge Models
Bartlomiej Sobieski, Matthew Tivnan, Yuang Wang et al.
Image Editing As Programs with Diffusion Models
Yujia Hu, Songhua Liu, Zhenxiong Tan et al.
Slow Transition to Low-Dimensional Chaos in Heavy-Tailed Recurrent Neural Networks
Eva Xie, Stefan Mihalas, Łukasz Kuśmierz
MaNGO — Adaptable Graph Network Simulators via Meta-Learning
Philipp Dahlinger, Tai Hoang, Denis Blessing et al.
On the Convergence of Single-Timescale Actor-Critic
Navdeep Kumar, Priyank Agrawal, Giorgia Ramponi et al.
RAST: Reasoning Activation in LLMs via Small-model Transfer
Siru Ouyang, Xinyu Zhu, Zilin Xiao et al.
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Adel Nabli, Louis Fournier, Pierre ERBACHER et al.
Scalable In-context Ranking with Generative Models
Nilesh Gupta, Chong You, Srinadh Bhojanapalli et al.
Transformers for Mixed-type Event Sequences
Felix Draxler, Yang Meng, Kai Nelson et al.
Scale-invariant attention
Ben Anson, Xi Wang, Laurence Aitchison
VA-GS: Enhancing the Geometric Representation of Gaussian Splatting via View Alignment
Qing Li, Huifang Feng, Xun Gong et al.
Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs
Richard Suwandi, Feng Yin, Juntao Wang et al.
Omni-Mol: Multitask Molecular Model for Any-to-any Modalities
Chengxin Hu, Hao Li, Yihe Yuan et al.
Factorio Learning Environment
Jack Hopkins, Mart Bakler, Akbir Khan
Learning to cluster neuronal function
Nina Nellen, Polina Turishcheva, Michaela Vystrčilová et al.
Provable Ordering and Continuity in Vision-Language Pretraining for Generalizable Embodied Agents
Zhizhen Zhang, Lei Zhu, Zhen Fang et al.
The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub et al.
Layer as Puzzle Pieces: Compressing Large Language Models through Layer Concatenation
Fei Wang, Li Shen, Liang Ding et al.
Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics
Salva Rühling Cachay, Miika Aittala, Karsten Kreis et al.
Variational Uncertainty Decomposition for In-Context Learning
I. Shavindra Jayasekera, Jacob Si, Filippo Valdettaro et al.
Logical Expressiveness of Graph Neural Networks with Hierarchical Node Individualization
Arie Soeteman, Balder ten Cate
HoloScene: Simulation‑Ready Interactive 3D Worlds from a Single Video
Hongchi Xia, Chih-Hao Lin, Hao-Yu Hsu et al.
Exploring the Translation Mechanism of Large Language Models
Hongbin Zhang, Kehai Chen, Xuefeng Bai et al.
PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs
Xinzhe Zheng, Hao Du, Fanding Xu et al.
Struct-Bench: A Benchmark for Differentially Private Structured Text Generation
Shuaiqi Wang, Vikas Raunak, Arturs Backurs et al.
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi et al.
A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
Etienne Boursier, Scott Pesme, Radu-Alexandru Dragomir
Chirality in Action: Time-Aware Video Representation Learning by Latent Straightening
Piyush Nitin Bagad, Andrew Zisserman
Cost-Sensitive Freeze-thaw Bayesian Optimization for Efficient Hyperparameter Tuning
Dong Bok Lee, Aoxuan Zhang, Byungjoo Kim et al.
Spectral Analysis of Diffusion Models with Application to Schedule Design
Roi Benita, Miki Elad, Joseph Keshet
DCA: Graph-Guided Deep Embedding Clustering for Brain Atlases
Mo WANG, Kaining Peng, Jingsheng Tang et al.
MixAT: Combining Continuous and Discrete Adversarial Training for LLMs
Csaba Dékány, Stefan Balauca, Dimitar I. Dimitrov et al.
PARTONOMY: Large Multimodal Models with Part-Level Visual Understanding
Ansel Blume, Jeonghwan Kim, Hyeonjeong Ha et al.
Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks
Francesco Cozzi, Marco Pangallo, Alan Perotti et al.
A TRIANGLE Enables Multimodal Alignment Beyond Cosine Similarity
Giordano Cicchetti, Eleonora Grassucci, Danilo Comminiello
Copresheaf Topological Neural Networks: A Generalized Deep Learning Framework
Mustafa Hajij, Lennart Bastian, Sarah Osentoski et al.
OVERT: A Benchmark for Over-Refusal Evaluation on Text-to-Image Models
Ziheng Cheng, Yixiao Huang, Hui Xu et al.
HMARL-CBF – Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems
H M Sabbir Ahmad, Ehsan Sabouni, Alexander Wasilkoff et al.
Faithful Group Shapley Value
Kiljae Lee, Ziqi Liu, Weijing Tang et al.
Edit Less, Achieve More: Dynamic Sparse Neuron Masking for Lifelong Knowledge Editing in LLMs
Jinzhe Liu, Junshu Sun, Shufan Shen et al.
Open-World Drone Active Tracking with Goal-Centered Rewards
Haowei Sun, Jinwu Hu, Zhirui Zhang et al.
Cost-aware LLM-based Online Dataset Annotation
Eray Can Elumar, Cem Tekin, Osman Yagan
Teaching Language Models to Reason with Tools
Chengpeng Li, Zhengyang Tang, Ziniu Li et al.
GRIP: A Graph-Based Reasoning Instruction Producer
Jiankang Wang, Jianjun Xu, Xiaorui Wang et al.
Learn2Mix: Training Neural Networks Using Adaptive Data Integration
Shyam Venkatasubramanian, Vahid Tarokh
Multivariate Latent Recalibration for Conditional Normalizing Flows
Victor Dheur, Souhaib Ben Taieb
S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning
Hanqing Zeng, Yinglong Xia, Zhuokai Zhao et al.
Neural Collapse in Cumulative Link Models for Ordinal Regression: An Analysis with Unconstrained Feature Model
Chuang Ma, Tomoyuki Obuchi, Toshiyuki Tanaka
How Memory in Optimization Algorithms Implicitly Modifies the Loss
Matias Cattaneo, Boris Shigida
ArchCAD-400K: A Large-Scale CAD drawings Dataset and New Baseline for Panoptic Symbol Spotting
Ruifeng Luo, Zhengjie Liu, Tianxiao Cheng et al.
Automatic Synthetic Data and Fine-grained Adaptive Feature Alignment for Composed Person Retrieval
Delong Liu, Haiwen Li, Zhaohui Hou et al.
Disentangling Latent Shifts of In-Context Learning with Weak Supervision
Josip Jukić, Jan Šnajder
A Unifying View of Linear Function Approximation in Off-Policy RL Through Matrix Splitting and Preconditioning
Zechen Wu, Amy Greenwald, Ronald Parr
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
Yang Peng, Kaicheng Jin, Liangyu Zhang et al.
Data Fusion for Partial Identification of Causal Effects
Quinn Lanners, Cynthia Rudin, Alexander Volfovsky et al.
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
Rui Xu, Dakuan Lu, Zicheng Zhao et al.
Efficient Adaptive Federated Optimization
Su Hyeong Lee, Sidharth Sharma, Manzil Zaheer et al.
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
Yanan Li, Fanxu Meng, Muhan Zhang et al.
Streaming Attention Approximation via Discrepancy Theory
Ekaterina Kochetkova, Kshiteej Jitesh Sheth, Insu Han et al.
Differentially Private Quantiles with Smaller Error
Jacob Imola, Fabrizio Boninsegna, Hannah Keller et al.
Conformal Arbitrage: Risk-Controlled Balancing of Competing Objectives in Language Models
William Overman, Mohsen Bayati
From Linear to Nonlinear: Provable Weak-to-Strong Generalization through Feature Learning
Junsoo Oh, Jerry Song, Chulhee Yun
Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models
Louis Bethune, David Vigouroux, Yilun Du et al.
Generalized Linear Mode Connectivity for Transformers
Alexander Theus, Alessandro Cabodi, Sotiris Anagnostidis et al.
Counterfactual reasoning: an analysis of in-context emergence
Moritz Miller, Bernhard Schölkopf, Siyuan Guo
Exploring Neural Granger Causality with xLSTMs: Unveiling Temporal Dependencies in Complex Data
Harsh Poonia, Felix Divo, Kristian Kersting et al.
Cross-Modal Representational Knowledge Distillation for Enhanced Spike-informed LFP Modeling
Eray Erturk, Saba Hashemi, Maryam Shanechi
Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering
Chenglin Fan, Dahoon Lee, Euiwoong Lee
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali Mahmutoğulları, Dimos Tsouros et al.
Many LLMs Are More Utilitarian Than One
Anita Keshmirian, Razan Baltaji, Babak Hemmatian et al.
COOPERA: Continual Open-Ended Human-Robot Assistance
Chenyang Ma, Kai Lu, Ruta Desai et al.
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn et al.
SAS: Simulated Attention Score
Chuanyang Zheng, Jiankai Sun, Yihang Gao et al.
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
Rikuto Kotoge, Zheng Chen, Tasuku Kimura et al.
Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models
Chantal Shaib, Vinith Suriyakumar, Byron Wallace et al.
Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, Andre Barreto et al.
Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining
Weiyi Wang, Junwei Deng, Yuzheng Hu et al.
Demystifying Network Foundation Models
Roman Beltiukov, Satyandra Guthula, Wenbo Guo et al.
Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search
Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou et al.
MPCache: MPC-Friendly KV Cache Eviction for Efficient Private LLM Inference
Wenxuan Zeng, Ye Dong, Jinjin Zhou et al.
DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
Hongshu Guo, Zeyuan Ma, Yining Ma et al.
AI Testing Should Account for Sophisticated Strategic Behaviour
Vojta Kovarik, Eric Chen, Sami Petersen et al.
FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
Dario Fenoglio, Mohan Li, Pietro Barbiero et al.
Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models
Yonggan Fu, Xin Dong, Shizhe Diao et al.
Fixed-Point RNNs: Interpolating from Diagonal to Dense
Sajad Movahedi, Felix Sarnthein, Nicola Muca Cirone et al.
ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding
Jialiang Kang, Han Shu, Wenshuo Li et al.
Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
Qiang Fu, Andre Wibisono
Detecting Generated Images by Fitting Natural Image Distributions
Yonggang Zhang, Jun Nie, Xinmei Tian et al.
Compositional Reasoning with Transformers, RNNs, and Chain of Thought
Gilad Yehudai, Noah Amsel, Joan Bruna
Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback
Shinji Ito, Kevin Jamieson, Haipeng Luo et al.
Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
Zhongzheng Qiao, Chenghao Liu, Yiming Zhang et al.
Dynamics of Spontaneous Topic Changes in Next Token Prediction with Self-Attention
Mumin Jia, Jairo Diaz-Rodriguez
GnnXemplar: Exemplars to Explanations - Natural Language Rules for Global GNN Interpretability
Burouj Armgaan, Eshan Jain, Harsh Pandey et al.
A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
Qingyue Zhang, Haohao Fu, Guanbo Huang et al.
RSCC: A Large-Scale Remote Sensing Change Caption Dataset for Disaster Events
Zhenyuan Chen, Chenxi Wang, Ningyu Zhang et al.
Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning
Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh et al.
Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics
Lorenzo Magnino, Kai Shao, Zida Wu et al.
Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation
Shiwei Li, Xiandi Luo, Haozhao Wang et al.
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective
Beatrix Nielsen, Emanuele Marconato, Andrea Dittadi et al.
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
Optimism Without Regularization: Constant Regret in Zero-Sum Games
John Lazarsfeld, Georgios Piliouras, Ryann Sim et al.
Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
Snir Hordan, Maya Bechler-Speicher, Gur Lifshitz et al.
BLINK-Twice: You see, but do you observe? A Reasoning Benchmark on Visual Perception
junyan ye, Dongzhi JIANG, Jun He et al.
Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
Parvin Nazari, Bojian Hou, Davoud Ataee Tarzanagh et al.
Towards Comprehensive Scene Understanding: Integrating First and Third-Person Views for LVLMs
Insu Lee, Wooje Park, Jaeyun Jang et al.
Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning
Jaesik Yoon, Hyeonseo Cho, Yoshua Bengio et al.
Attack via Overfitting: 10-shot Benign Fine-tuning to Jailbreak LLMs
Zhixin Xie, Xurui Song, Jun Luo
Feedback-Aware MCTS for Goal-Oriented Information Seeking
Harshita Chopra, Chirag Shah
HYPRL: Reinforcement Learning of Control Policies for Hyperproperties
Tzu-Han Hsu, Arshia Rafieioskouei, Borzoo Bonakdarpour
IMPROVED LEARNING THEORY FOR KERNEL DISTRIBUTION REGRESSION WITH TWO-STAGE SAMPLING
Alberto González-Sanz, François Bachoc, Jean-Michel Loubes et al.
The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
Moritz Stargalla, Christoph Hertrich, Daniel Reichman
Optimal Rates in Continual Linear Regression via Increasing Regularization
Ran Levinstein, Amit Attia, Matan Schliserman et al.
Benchmarking Spatiotemporal Reasoning in LLMs and Reasoning Models: Capabilities and Challenges
Pengrui Quan, Brian Wang, Kang Yang et al.
Influence Guided Context Selection for Effective Retrieval-Augmented Generation
Jiale Deng, Yanyan Shen, Ziyuan Pei et al.
Group-Level Data Selection for Efficient Pretraining
Zichun Yu, Fei Peng, Jie Lei et al.
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
Reda Marzouk, Shahaf Bassan, Guy Katz
ShiQ: Bringing back Bellman to LLMs
Pierre Clavier, Nathan Grinsztajn, Raphaël Avalos et al.
LinEAS: End-to-end Learning of Activation Steering with a Distributional Loss
Pau Rodriguez, Michal Klein, Eleonora Gualdoni et al.
FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models
Zihao Fu, Ryan Brown, Shun Shao et al.
Sample and Map from a Single Convex Potential: Generation using Conjugate Moment Measures
Nina Vesseron, Louis Bethune, Marco Cuturi
Foresight: Adaptive Layer Reuse for Accelerated and High-Quality Text-to-Video Generation
Muhammad Adnan, Nithesh Kurella, Akhil Arunkumar et al.
Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
Yang Qiu, Yixiong Zou, Jun Wang et al.
Practical Bayes-Optimal Membership Inference Attacks
Marcus Lassila, Johan Oestman, Khac-Hoang Ngo et al.