Most Cited ICML "conditional independence assumption" Papers
5,975 papers found • Page 11 of 30
Conference
Telling Peer Direct Effects from Indirect Effects in Observational Network Data
Xiaojing Du, Jiuyong Li, Debo Cheng et al.
Weight matrices compression based on PDB model in deep neural networks
Xiaoling Wu, Junpeng Zhu, Zeng Li
IMTS is Worth Time $\times$ Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
Zhangyi Hu, Jiemin Wu, Hua XU et al.
L-Diffusion: Laplace Diffusion for Efficient Pathology Image Segmentation
Weihan Li, Linyun Zhou, YangJian et al.
DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
Simin Chen, Pranav Pusarla, Baishakhi Ray
A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
Zhengzheng Lou, Hang Xue, Chaoyang Zhang et al.
Generalized additive models via direct optimization of regularized decision stump forests
Magzhan Gabidolla, Miguel Carreira-Perpinan
Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
Gaozheng Pei, Ke Ma, Yingfei Sun et al.
Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
Zhuocheng Gong, Jian Guan, Wei Wu et al.
BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
Xu Wang, Yan Hu, Wenyu Du et al.
Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization
Yucheng Yang, Tianyi Zhou, Mykola Pechenizkiy et al.
Long-Form Speech Generation with Spoken Language Models
Se Jin Park, Julian Salazar, Aren Jansen et al.
Sampling Binary Data by Denoising through Score Functions
Francis Bach, Saeed Saremi
Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
Han Jiang, Xiaoyuan Yi, Zhihua Wei et al.
Demystifying Singular Defects in Large Language Models
Haoqi Wang, Tong Zhang, Mathieu Salzmann
ToMA: Token Merge with Attention for Diffusion Models
Wenbo Lu, Shaoyi Zheng, Yuxuan Xia et al.
Decoupled SGDA for Games with Intermittent Strategy Communication
Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.
Graph Inverse Style Transfer for Counterfactual Explainability
Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
Ce Zhang, Yixin Han, Yafei Wang et al.
CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
Zongzhen Yang, Binhang Qi, Hailong Sun et al.
Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations
Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.
Average Sensitivity of Hierarchical $k$-Median Clustering
Shijie Li, Weiqiang He, Ruobing Bai et al.
You Get What You Give: Reciprocally Fair Federated Learning
Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.
Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling
Xiang Hu, Zhihao Teng, Jun Zhao et al.
Sounding that Object: Interactive Object-Aware Image to Audio Generation
Tingle Li, Baihe Huang, Xiaobin Zhuang et al.
Anytime-Constrained Equilibria in Polynomial Time
Jeremy McMahan
Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates
Yunfei Huang, David S. Greenberg
Controlling Neural Collapse Enhances Out-of-Distribution Detection and Transfer Learning
Md Yousuf Harun, Jhair Gallardo, Christopher Kanan
Cross-Modal Alignment via Variational Copula Modelling
Feng Wu, Tsai Hor Chan, Fuying Wang et al.
Fourier Position Embedding: Enhancing Attention’s Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv et al.
Dynamic Similarity Graph Construction with Kernel Density Estimation
Steinar Laenen, Peter Macgregor, He Sun
Cover learning for large-scale topology representation
Luis Scoccola, Uzu Lim, Heather Harrington
Extreme Value Policy Optimization for Safe Reinforcement Learning
Shiqing Gao, Yihang Zhou, Shuai Shao et al.
Meta-Black-Box-Optimization through Offline Q-function Learning
Zeyuan Ma, Zhiguang Cao, Zhou Jiang et al.
Confounder-Free Continual Learning via Recursive Feature Normalization
Yash Shah, Camila Gonzalez, MohammadHassan Abbasi et al.
Disentangled Graph Spectral Domain Adaptation
Liang Yang, Xin Chen, Jiaming Zhuo et al.
The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking
Yuchun Miao, Sen Zhang, Liang Ding et al.
Flexibility-conditioned protein structure design with flow matching
Vsevolod Viliuga, Leif Seute, Nicolas Wolf et al.
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
Sungnyun Kim, Kangwook Jang, Sangmin Bae et al.
Decision-aware Training of Spatiotemporal Forecasting Models to Select a Top-K Subset of Sites for Intervention
Kyle Heuton, Frederick Muench, Shikhar Shrestha et al.
GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning
Zhun Mou, Bin Xia, Zhengchao Huang et al.
Label Distribution Propagation-based Label Completion for Crowdsourcing
Tong Wu, Liangxiao Jiang, Wenjun Zhang et al.
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang, Yu-Jie Zhang, Peng Zhao et al.
Compressing tree ensembles through Level-wise Optimization and Pruning
Laurens Devos, Timo Martens, Deniz Oruc et al.
Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk, Siu Lun Chau, Francois-Xavier Briol et al.
In-Context Learning as Conditioned Associative Memory Retrieval
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu et al.
Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
junmin zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian et al.
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making
Yucen Wang, Rui Yu, Shenghua Wan et al.
The Limits of Predicting Agents from Behaviour
Alexis Bellot, Jonathan Richens, Tom Everitt
Graph-constrained Reasoning: Faithful Reasoning on Knowledge Graphs with Large Language Models
Linhao Luo, Zicheng Zhao, Reza Haffari et al.
Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory
Mason O. Smith, Wenlong Zhang
Zero-Shot Offline Imitation Learning via Optimal Transport
Thomas Rupf, Marco Bagatella, Nico Gürtler et al.
POQD: Performance-Oriented Query Decomposer for Multi-vector retrieval
Yaoyang Liu, Junlin Li, Yinjun Wu et al.
Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model
SHEN FEI, Cong Wang, Junyao Gao et al.
AnyEdit: Edit Any Knowledge Encoded in Language Models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang et al.
Multi-Turn Code Generation Through Single-Step Rewards
Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen et al.
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning
Thomas T. Zhang, Behrad Moniri, Ansh Nagwekar et al.
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance
Guoqing Chao, Zhenghao Zhang, Lei Meng et al.
Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla
Compositional Condition Question Answering in Tabular Understanding
Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan et al.
MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition
Wei Li, Lujun Li, Hao Gu et al.
Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff et al.
Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
Youran Dong, Junfeng Yang, Wei Yao et al.
Reinforcement Learning with Adaptive Reward Modeling for Expensive-to-Evaluate Systems
Hongyuan Su, Yu Zheng, Yuan Yuan et al.
Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph
Zhiqiang Wang, Jianghao Wen, Jianqing Liang
Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching
Amit Attia, Ofir Gaash, Tomer Koren
Lightweight-Mark: Rethinking Deep Learning-Based Watermarking
Yupeng Qiu, Han Fang, Ee-Chien Chang
Offline Learning for Combinatorial Multi-armed Bandits
Xutong Liu, Xiangxiang Dai, Jinhang Zuo et al.
SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
Haoquan Fang, Markus Grotz, Wilbert Pumacay et al.
FLAM: Frame-Wise Language-Audio Modeling
Yusong Wu, Christos Tsirigotis, Ke Chen et al.
Splitting & Integrating: Out-of-Distribution Detection via Adversarial Gradient Attribution
Jiayu Zhang, Xinyi Wang, Zhibo Jin et al.
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin et al.
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.
Piloting Structure-Based Drug Design via Modality-Specific Optimal Schedule
Keyue Qiu, Yuxuan Song, Zhehuan Fan et al.
SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
Yong Liu, Di Fu, Shenggan Cheng et al.
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
Jacopo Talpini, Marco Savi, Giovanni Neglia
Language Models as Implicit Tree Search
Ziliang Chen, Zhao-Rong Lai, Yufeng Yang et al.
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Ron Shapira Weber, shahar benishay, Andrey Lavrinenko et al.
Exploring Representations and Interventions in Time Series Foundation Models
Michal Wilinski, Mononito Goswami, Willa Potosnak et al.
Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
Yiming Yang, Xiaoyuan Cheng, Daniel Giles et al.
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Ningyi Liao, Zihao Yu, Ruixiao Zeng et al.
The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models Via Visual Information Steering
Zhuowei Li, Haizhou Shi, Yunhe Gao et al.
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le Tuyet Nhi PHAM, Dario Shariatian, Antonio Ocello et al.
Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction
Yiting He, Zhishuai Liu, Weixin Wang et al.
Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu et al.
Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning
Wenke Huang, Jian Liang, Guancheng Wan et al.
SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields
David K Park, Xihaier Luo, Guang Zhao et al.
Towards a Formal Theory of Representational Compositionality
Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio et al.
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel Images
Zhengrui Guo, Qichen Sun, Jiabo MA et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Li, Daohan Lu, Polina Kirichenko et al.
What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning?
Katie Kang, Amrith Setlur, Dibya Ghosh et al.
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
Harry Mead, Clarissa Costen, Bruno Lacerda et al.
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
Wenju Sun, Qingyong Li, Yangliao Geng et al.
Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
Yucheng Hu, Yanjiang Guo, Pengchao Wang et al.
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.
Controlling Large Language Model with Latent Action
Chengxing Jia, Ziniu Li, Pengyuan Wang et al.
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
Yifan Sun, Han Wang, Dongbai Li et al.
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong, Jian Cheng, Xi Zhang
Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time
Mohamad Chehade, Soumya Suvra Ghosal, Souradip Chakraborty et al.
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams
Lin Zhu, Xiantao Ma, Xiao Wang et al.
Hypo3D: Exploring Hypothetical Reasoning in 3D
Ye Mao, Weixun Luo, Junpeng Jing et al.
Efficient and Separate Authentication Image Steganography Network
Junchao Zhou, Yao Lu, Jie Wen et al.
Learning Fused State Representations for Control from Multi-View Observations
Zeyu Wang, Yao-Hui Li, Xin Li et al.
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
Large Language Models to Diffusion Finetuning
Edoardo Cetin, Tianyu Zhao, Yujin Tang
SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space
Xupeng Zhu, Fan Wang, Robin Walters et al.
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber et al.
CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries
Ni Mu, Hao Hu, Xiao Hu et al.
SketchDNN: Joint Continuous-Discrete Diffusion for CAD Sketch Generation
Sathvik Chereddy, John Femiani
Compressed Image Generation with Denoising Diffusion Codebook Models
Guy Ohayon, Hila Manor, Tomer Michaeli et al.
The Limits of Tractable Marginalization
Oliver Broadrick, Sanyam Agarwal, Guy Van den Broeck et al.
Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions
Tejas Jayashankar, Jongha (Jon) Ryu, Gregory Wornell
Nonparametric Identification of Latent Concepts
Yujia Zheng, Shaoan Xie, Kun Zhang
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida et al.
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos et al.
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Peng, Adriel Kuek et al.
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
Goal-Oriented Skill Abstraction for Offline Multi-Task Reinforcement Learning
Jinmin He, Kai Li, Yifan Zang et al.
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
Wenjing Yan, Xiangyu Zhong, Xiaolu Wang et al.
Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
Tong Yang, Bo Dai, Lin Xiao et al.
Hyperbolic-PDE GNN: Spectral Graph Neural Networks in the Perspective of A System of Hyperbolic Partial Differential Equations
Juwei Yue, Haikuo Li, Jiawei Sheng et al.
Teaching Transformers Causal Reasoning through Axiomatic Training
Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.
Steer LLM Latents for Hallucination Detection
Seongheon Park, Xuefeng Du, Min-Hsuan Yeh et al.
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
Allen Nie, Yi Su, Bo Chang et al.
Curse of High Dimensionality Issue in Transformer for Long Context Modeling
Shuhai Zhang, Zeng You, Yaofo Chen et al.
Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
Nabeel Seedat, Mihaela van der Schaar
LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
Peer Nagy, Sascha Frey, Kang Li et al.
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Zhao, Xinai Lu et al.
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
Walter Mayor, Johan Obando-Ceron, Aaron Courville et al.
Detecting Strategic Deception with Linear Probes
Nicholas Goldowsky-Dill, Bilal Chughtai, Stefan Heimersheim et al.
Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny et al.
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory
Feifei Li, Mi Zhang, Zhaoxiang Wang et al.
Measuring In-Context Computation Complexity via Hidden State Prediction
Vincent Herrmann, Róbert Csordás, Jürgen Schmidhuber
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
Changdae Oh, zhen fang, Shawn Im et al.
Learning Extrapolative Sequence Transformations from Markov Chains
Sophia Hager, Aleem Khan, Andrew Wang et al.
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.
Representative Language Generation
Charlotte Peale, Vinod Raman, Omer Reingold
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella, Simon Bing, Jakob Runge
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.
An analytic theory of creativity in convolutional diffusion models
Mason Kamb, Surya Ganguli
Conservative Offline Goal-Conditioned Implicit V-Learning
Ke Kaiqiang, qian lin, Zongkai Liu et al.
SkipGPT: Each Token is One of a Kind
Anhao Zhao, Fanghua Ye, Yingqi Fan et al.
A Model of Place Field Reorganization During Reward Maximization
M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth et al.
Online Episodic Convex Reinforcement Learning
Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard et al.
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong
Multiaccuracy and Multicalibration via Proxy Groups
Beepul Bharti, Mary Clemens-Sewall, Paul H. Yi et al.
Synthetic Text Generation for Training Large Language Models via Gradient Matching
Dang Nguyen, Zeman Li, MohammadHossein Bateni et al.
Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
Penghao Wu, Lewei Lu, Ziwei Liu
Scalable Approximation Algorithms for $p$-Wasserstein Distance and Its Variants
Nathaniel Lahn, Sharath Raghvendra, Emma Saarinen et al.
Towards flexible perception with visual memory
Robert Geirhos, Priyank Jaini, Austin Stone et al.
SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models
Yung-Sung Chuang, Benjamin Cohen-Wang, Shannon Shen et al.
Geometry-Informed Neural Networks
Arturs Berzins, Andreas Radler, Eric Volkmann et al.
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems
Botao Chen, Jongyeong Lee, Junya Honda
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca et al.
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
Hila Chefer, Uriel Singer, Amit Zohar et al.
Concept Reachability in Diffusion Models: Beyond Dataset Constraints
Marta Aparicio Rodriguez, Xenia Miscouridou, Anastasia Borovykh
Unifying Knowledge from Diverse Datasets to Enhance Spatial-Temporal Modeling: A Granularity-Adaptive Geographical Embedding Approach
Zhigaoyuan Wang, Ying Sun, Hengshu Zhu
FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
Zhen Sun, Lei Tan, Yunhang Shen et al.
Discovering Symbolic Cognitive Models from Human and Animal Behavior
Pablo Samuel Castro, Nenad Tomasev, Ankit Anand et al.
Implicit Language Models are RNNs: Balancing Parallelization and Expressivity
Mark Schoene, Babak Rahmani, Heiner Kremer et al.
A Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
Muhammed Ustaomeroglu, Guannan Qu
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Universal Neural Optimal Transport
Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson et al.
WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
Chinmay Savadikar, Xi Song, Tianfu Wu
Testing Conditional Mean Independence Using Generative Neural Networks
Yi Zhang, Linjun Huang, Yun Yang et al.
Position: AI Safety should prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
General agents need world models
Jonathan Richens, Tom Everitt, David Abel
Physics-Informed Weakly Supervised Learning For Interatomic Potentials
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
Statistical Test for Feature Selection Pipelines by Selective Inference
Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu, Zhichao Huang, Mathieu Salzmann et al.
Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models
Shuoyuan Wang, Sharon Li, Hongxin Wei
Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
Daniel Franzen, Jan Disselhoff, David Hartmann
Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering
Zihan Song, Xin Wang, Zi Qian et al.
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Roch, George Atia, Yue Wang
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Leo de Castro, Daniel Escudero, Adya Agrawal et al.
How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical Perspective
Jing Qiao, Yu Liu, YUAN YUAN et al.
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers et al.
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Rohan Deb, Kiran Thekumparampil, Kousha Kalantari et al.
Neural Solver Selection for Combinatorial Optimization
Chengrui Gao, Haopu Shang, Ke Xue et al.
David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training
Weijian Luo, colin zhang, Debing Zhang et al.
KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors
Benson Chen, Tomasz Danel, Gabriel Dreiman et al.
System-Aware Unlearning Algorithms: Use Lesser, Forget Faster
Linda Lu, Ayush Sekhari, Karthik Sridharan
Closed-form Solutions: A New Perspective on Solving Differential Equations
Shu Wei, Yanjie Li, Lina Yu et al.
FedClean: A General Robust Label Noise Correction for Federated Learning
Xiaoqian Jiang, Jing Zhang
Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation
Laura Zheng, Wenjie Wei, Tony Wu et al.
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.
Learning with Exact Invariances in Polynomial Time
Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.
Banyan: Improved Representation Learning with Explicit Structure
Mattia Opper, Siddharth N
Understanding the Logic of Direct Preference Alignment through Logic
Kyle Richardson, Vivek Srikumar, Ashish Sabharwal
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations
Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda et al.
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
Jiachen Hu, Rui Ai, Han Zhong et al.
NestQuant: nested lattice quantization for matrix products and LLMs
Semyon Savkin, Eitan Porat, Or Ordentlich et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.