Most Cited ICML "latent refinement" Papers
5,975 papers found • Page 2 of 30
Conference
Synthesizing Privacy-Preserving Text Data via Finetuning *without* Finetuning Billion-Scale LLMs
Bowen Tan, Zheng Xu, Eric Xing et al.
Scaling Laws for Differentially Private Language Models
Ryan McKenna, Yangsibo Huang, Amer Sinha et al.
On Temperature Scaling and Conformal Prediction of Deep Classifiers
Lahav Dabah, Tom Tirer
Update Your Transformer to the Latest Release: Re-Basin of Task Vectors
Filippo Rinaldi, Giacomo Capitani, Lorenzo Bonicelli et al.
Strategy Coopetition Explains the Emergence and Transience of In-Context Learning
Aaditya Singh, Ted Moskovitz, Sara Dragutinović et al.
Not all solutions are created equal: An analytical dissociation of functional and representational similarity in deep linear neural networks
Lukas Braun, Erin Grant, Andrew Saxe
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
Seongho Son, William Bankes, Sayak Ray Chowdhury et al.
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Qinglin Zhu, Runcong Zhao, Hanqi Yan et al.
Effective and Efficient Masked Image Generation Models
Zebin You, Jingyang Ou, Xiaolu Zhang et al.
Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments
Yun Qu, Cheems Wang, Yixiu Mao et al.
GaussMark: A Practical Approach for Structural Watermarking of Language Models
Adam Block, Alexander Rakhlin, Ayush Sekhari
BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning
Han Zhong, Yutong Yin, Shenao Zhang et al.
Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection
Matteo Zecchin, Sangwoo Park, Osvaldo Simeone
De-mark: Watermark Removal in Large Language Models
Ruibo Chen, Yihan Wu, Junfeng Guo et al.
MoEQuant: Enhancing Quantization for Mixture-of-Experts Large Language Models via Expert-Balanced Sampling and Affinity Guidance
Zhixuan Chen, Xing Hu, Dawei Yang et al.
A Closer Look at Multimodal Representation Collapse
Abhra Chaudhuri, Anjan Dutta, Tu Bui et al.
Gaussian Mixture Flow Matching Models
Hansheng Chen, Kai Zhang, Hao Tan et al.
AutoAdvExBench: Benchmarking Autonomous Exploitation of Adversarial Example Defenses
Nicholas Carlini, Edoardo Debenedetti, Javier Rando et al.
LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
Yuanhe Zhang, Fanghui Liu, Yudong Chen
Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens
Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen et al.
Self-Discriminative Modeling for Anomalous Graph Detection
Jinyu Cai, Yunhe Zhang, Jicong Fan
Secant Line Search for Frank-Wolfe Algorithms
Deborah Hendrych, Sebastian Pokutta, Mathieu Besançon et al.
Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
Artavazd Maranjyan, Alexander Tyurin, Peter Richtarik
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks
Tuomas Oikarinen, Ge Yan, Lily Weng
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
Rudy Morel, Jiequn Han, Edouard Oyallon
Data-Juicer Sandbox: A Feedback-Driven Suite for Multimodal Data-Model Co-development
Daoyuan Chen, Haibin Wang, Yilun Huang et al.
Position: We Need An Algorithmic Understanding of Generative AI
Oliver Eberle, Thomas McGee, Hamza Giaffar et al.
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling
Alexander Capstick, Rahul G. Krishnan, Payam Barnaghi
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
Max Wilcoxson, Qiyang Li, Kevin Frans et al.
Ultra-Resolution Adaptation with Ease
Ruonan Yu, Songhua Liu, Zhenxiong Tan et al.
Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
Chenbei Lu, Laixi Shi, Zaiwei Chen et al.
Perception in Reflection
Yana Wei, Liang Zhao, Kangheng Lin et al.
Robust and Conjugate Spatio-Temporal Gaussian Processes
William Laplante, Matias Altamirano, Andrew Duncan et al.
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
Loss Functions and Operators Generated by f-Divergences
Vincent Roulet, Tianlin Liu, Nino Vieillard et al.
Impossible Videos
Zechen Bai, Hai Ci, Mike Zheng Shou
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
David Heurtel-Depeiges, Anian Ruoss, Joel Veness et al.
Learning Safety Constraints for Large Language Models
Xin Chen, Yarden As, Andreas Krause
Doubly Robust Conformalized Survival Analysis with Right-Censored Data
Matteo Sesia, vladimir svetnik
Privacy Attacks on Image AutoRegressive Models
Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch et al.
Towards Robustness and Explainability of Automatic Algorithm Selection
Xingyu Wu, Jibin Wu, Yu Zhou et al.
Selective Prompt Anchoring for Code Generation
Yuan Tian, Tianyi Zhang
Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
Minh-Tung Luu, Younghwan Lee, Donghoon Lee et al.
Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation
Jingyu Liu, Beidi Chen, Ce Zhang
Vision-Language Models Create Cross-Modal Task Representations
Grace Luo, Trevor Darrell, Amir Bar
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang et al.
Componential Prompt-Knowledge Alignment for Domain Incremental Learning
Kunlun Xu, Xu Zou, Gang Hua et al.
SafetyAnalyst: Interpretable, Transparent, and Steerable Safety Moderation for AI Behavior
Jing-Jing Li, Valentina Pyatkin, Max Kleiman-Weiner et al.
Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang et al.
Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Tianyuan Zou, Yang Liu, Peng Li et al.
XAttnMark: Learning Robust Audio Watermarking with Cross-Attention
Yixin Liu, Lie Lu, Jihui Jin et al.
Position: The Most Expensive Part of an LLM *should* be its Training Data
Nikhil Kandpal, Colin Raffel
SEMU: Singular Value Decomposition for Efficient Machine Unlearning
Marcin Sendera, Łukasz Struski, Kamil Książek et al.
Understanding the Limits of Deep Tabular Methods with Temporal Shift
Haorun Cai, Han-Jia Ye
DEALing with Image Reconstruction: Deep Attentive Least Squares
Mehrsa Pourya, Erich Kobler, Michael Unser et al.
PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS
Hongyi Liu, Rajarshi Saha, Zhen Jia et al.
Task Generalization with Autoregressive Compositional Structure: Can Learning from $D$ Tasks Generalize to $D^T$ Tasks?
Amirhesam Abedsoltan, Huaqing Zhang, Kaiyue Wen et al.
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
Clément Bonet, Christophe Vauthier, Anna Korba
Understanding and Mitigating Memorization in Diffusion Models for Tabular Data
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen et al.
Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
Hang Zhou, Yuezhou Ma, Haixu Wu et al.
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Zhitong Xu, Da Long, Yiming Xu et al.
QT-DoG: Quantization-Aware Training for Domain Generalization
Saqib Javed, Hieu Le, Mathieu Salzmann
EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
Mujin Cheon, Jay Lee, Dong-Yeun Koh et al.
Volume Optimality in Conformal Prediction with Structured Prediction Sets
Chao Gao, Liren Shan, Vaidehi Srinivas et al.
Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius et al.
Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
Jing Yang
No-Regret is not enough! Bandits with General Constraints through Adaptive Regret Minimization
Martino Bernasconi, Matteo Castiglioni, Andrea Celli
TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
Xiaowen Ma, Zhen-Liang Ni, Shuai Xiao et al.
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
Guozheng Ma, Lu Li, Zilin Wang et al.
Causal Discovery from Conditionally Stationary Time Series
Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra et al.
Language Models over Canonical Byte-Pair Encodings
Tim Vieira, Tianyu Liu, Clemente Pasti et al.
Activation Space Interventions Can Be Transferred Between Large Language Models
Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash et al.
Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning
Liang CHEN, Xueting Han, Li Shen et al.
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti et al.
Regress, Don't Guess: A Regression-like Loss on Number Tokens for Language Models
Jonas Zausinger, Lars Pennig, Anamarija Kozina et al.
HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding
Rui Yang, Lin Song, Yicheng Xiao et al.
ROPO: Robust Preference Optimization for Large Language Models
Xize Liang, Chao Chen, Shuang Qiu et al.
Parameter-Efficient Fine-Tuning of State Space Models
Kevin Galim, Wonjun Kang, Yuchen Zeng et al.
SK-VQA: Synthetic Knowledge Generation at Scale for Training Context-Augmented Multimodal LLMs
Xin Su, Man Luo, Kris Pan et al.
From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information?
Zhanke Zhou, Xiao Feng, Zhaocheng Zhu et al.
Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
Cheng Tang, Zhishuai Liu, Pan Xu
Overestimation in LLM Evaluation: A Controlled Large-Scale Study on Data Contamination’s Impact on Machine Translation
Muhammed Yusuf Kocyigit, Eleftheria Briakou, Daniel Deutsch et al.
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun et al.
Variational Control for Guidance in Diffusion Models
Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler et al.
Efficient Distributed Optimization under Heavy-Tailed Noise
Su Hyeong Lee, Manzil Zaheer, Tian Li
RZ-NAS: Enhancing LLM-guided Neural Architecture Search via Reflective Zero-Cost Strategy
Zipeng Ji, Guanghui Zhu, Chunfeng Yuan et al.
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost
Sen Xing, Muyan Zhong, Zeqiang Lai et al.
Hyperband-based Bayesian Optimization for Black-box Prompt Selection
Lennart Schneider, Martin Wistuba, Aaron Klein et al.
LLM-Augmented Chemical Synthesis and Design Decision Programs
Haorui Wang, Jeff Guo, Lingkai Kong et al.
SAE-V: Interpreting Multimodal Models for Enhanced Alignment
Hantao Lou, Changye Li, Jiaming Ji et al.
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Daniil Laptev, Nikita Balagansky, Yaroslav Aksenov et al.
Enhancing Statistical Validity and Power in Hybrid Controlled Trials: A Randomization Inference Approach with Conformal Selective Borrowing
Ke Zhu, Shu Yang, Xiaofei Wang
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen et al.
Rethinking Chain-of-Thought from the Perspective of Self-Training
Zongqian Wu, Baoduo Xu, Ruochen Cui et al.
Prediction-Powered E-Values
Daniel Csillag, Claudio Struchiner, Guilherme Tegoni Goedert
Hierarchical Graph Tokenization for Molecule-Language Alignment
Yongqiang Chen, QUANMING YAO, Juzheng Zhang et al.
PatchPilot: A Cost-Efficient Software Engineering Agent with Early Attempts on Formal Verification
Hongwei Li, Yuheng Tang, Shiqi Wang et al.
When Maximum Entropy Misleads Policy Optimization
Ruipeng Zhang, Ya-Chien Chang, Sicun Gao
Learning from Integral Losses in Physics Informed Neural Networks
Ehsan Saleh, Saba Ghaffari, Timothy Bretl et al.
Learning Distances from Data with Normalizing Flows and Score Matching
Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr et al.
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
Lucy Farnik, Tim Lawson, Conor Houghton et al.
Tree-Sliced Wasserstein Distance with Nonlinear Projection
Thanh Tran, Viet Hoang Tran, Thanh Chu et al.
In-Context Denoising with One-Layer Transformers: Connections between Attention and Associative Memory Retrieval
Matthew Smart, Alberto Bietti, Anirvan Sengupta
Correlated Errors in Large Language Models
Elliot Myunghoon Kim, Avi Garg, Kenny Peng et al.
Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo
Idan Achituve, Hai Victor Habi, Amir Rosenfeld et al.
Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
Alessandro Palma, Sergei Rybakov, Leon Hetzel et al.
MERGE$^3$: Efficient Evolutionary Merging on Consumer-grade GPUs
Tommaso Mencattini, Adrian Robert Minut, Donato Crisostomi et al.
DOLPHIN: A Programmable Framework for Scalable Neurosymbolic Learning
Aaditya Naik, Jason Liu, Claire Wang et al.
General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
Kwangjun Ahn, Gagik Magakyan, Ashok Cutkosky
Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
Sangyeon Park, Isaac Han, Seungwon Oh et al.
Features are fate: a theory of transfer learning in high-dimensional regression
Javan Tahir, Surya Ganguli, Grant Rotskoff
One Leaf Reveals the Season: Occlusion-Based Contrastive Learning with Semantic-Aware Views for Efficient Visual Representation
Xiaoyu Yang, Lijian Xu, Hongsheng Li et al.
Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
Shenao Zhang, Zhihan Liu, Boyi Liu et al.
TTFSFormer: A TTFS-based Lossless Conversion of Spiking Transformer
Lusen Zhao, Zihan Huang, Ding Jianhao et al.
What makes an Ensemble (Un) Interpretable?
Shahaf Bassan, Guy Amir, Meirav Zehavi et al.
Temporal Difference Flows
Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni et al.
Understanding Generalization in Quantum Machine Learning with Margins
TAK HUR, Daniel Kyungdeock Park
EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
Dong HUANG, Guangtao Zeng, Jianbo Dai et al.
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Wei Liu, Zhongyu Niu, Lang Gao et al.
Shielded Diffusion: Generating Novel and Diverse Images using Sparse Repellency
Michael Kirchhof, James Thornton, Louis Béthune et al.
Aligning Multimodal Representations through an Information Bottleneck
Antonio Almudévar, Jose Miguel Hernandez-Lobato, Sameer Khurana et al.
On the Robustness of Reward Models for Language Model Alignment
Jiwoo Hong, Noah Lee, Eunki Kim et al.
PINNsAgent: Automated PDE Surrogation with Large Language Models
Qingpo Wuwu, Chonghan Gao, Tianyu Chen et al.
KV Shifting Attention Enhances Language Modeling
Mingyu Xu, Bingning Wang, Weipeng Chen
Fundamental Limits of Visual Autoregressive Transformers: Universal Approximation Abilities
Yifang Chen, Xiaoyu Li, Yingyu Liang et al.
Predicting mutational effects on protein binding from folding energy
Arthur Deng, Karsten Householder, Fang Wu et al.
Provable Maximum Entropy Manifold Exploration via Diffusion Models
Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh et al.
PARQ: Piecewise-Affine Regularized Quantization
Lisa Jin, Jianhao Ma, Zechun Liu et al.
Scaling Laws for Floating–Point Quantization Training
Xingwu Sun, Shuaipeng Li, Ruobing Xie et al.
Importance Corrected Neural JKO Sampling
Johannes Hertrich, Robert Gruhlke
ELITE: Enhanced Language-Image Toxicity Evaluation for Safety
Wonjun Lee, Doehyeon Lee, Eugene Choi et al.
Embedding Safety into RL: A New Take on Trust Region Methods
Nikola Milosevic, Johannes Müller, Nico Scherf
Looking Beyond the Top-1: Transformers Determine Top Tokens in Order
Daria Lioubashevski, Tomer Schlank, Gabriel Stanovsky et al.
Towards Trustworthy Federated Learning with Untrusted Participants
Youssef Allouah, Rachid Guerraoui, John Stephan
On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains
Xun Xian, Ganghua Wang, Xuan Bi et al.
When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets
Chen Zeno, Hila Manor, Gregory Ongie et al.
Scaling Laws for Upcycling Mixture-of-Experts Language Models
Seng Pei Liew, Takuya Kato, Sho Takase
Test-Time Training Provably Improves Transformers as In-context Learners
Halil Alperen Gozeten, Muhammed Emrullah Ildiz, Xuechen Zhang et al.
GAPrompt: Geometry-Aware Point Cloud Prompt for 3D Vision Model
Zixiang Ai, Zichen Liu, Yuanhang Lei et al.
LLMScan: Causal Scan for LLM Misbehavior Detection
Mengdi Zhang, Goh Kiat, Peixin Zhang et al.
Continuous Visual Autoregressive Generation via Score Maximization
Chenze Shao, Fandong Meng, Jie Zhou
On Volume Minimization in Conformal Regression
Batiste Le Bars, Pierre Humbert
Constrained Belief Updates Explain Geometric Structures in Transformer Representations
Mateusz Piotrowski, Paul Riechers, Daniel Filan et al.
Contextual Online Decision Making with Infinite-Dimensional Functional Regression
Haichen Hu, Rui Ai, Stephen Bates et al.
DipLLM: Fine-Tuning LLM for Strategic Decision-making in Diplomacy
Kaixuan Xu, Jiajun Chai, Sicheng Li et al.
Automatically Identify and Rectify: Robust Deep Contrastive Multi-view Clustering in Noisy Scenarios
xihong yang, Siwei Wang, Fangdi Wang et al.
Ranked Entropy Minimization for Continual Test-Time Adaptation
Jisu Han, Jaemin Na, Wonjun Hwang
In-Context Learning and Occam's Razor
Eric Elmoznino, Tom Marty, Tejas Kasetty et al.
(How) Can Transformers Predict Pseudo-Random Numbers?
Tao Tao, Darshil Doshi, Dayal Singh Kalra et al.
Position: Build Agent Advocates, Not Platform Agents
Sayash Kapoor, Noam Kolt, Seth Lazar
MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
Zhicheng Zhang, Wuyou Xia, Chenxi Zhao et al.
On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists
Dongyang Fan, Bettina Messmer, Nikita Doikov et al.
Cannot See the Forest for the Trees: Invoking Heuristics and Biases to Elicit Irrational Choices of LLMs
Haoming Yang, Ke Ma, Xiaojun Jia et al.
Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
Ali Behrouz, Ali Parviz, Mahdi Karami et al.
FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
Arya Fayyazi, Mehdi Kamal, Massoud Pedram
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis
Yinghao Li, Rithesh Kumar, Zeyu Jin
Task-Agnostic Pre-training and Task-Guided Fine-tuning for Versatile Diffusion Planner
Chenyou Fan, Chenjia Bai, Zhao Shan et al.
Collapse-Proof Non-Contrastive Self-Supervised Learning
EMANUELE SANSONE, Tim Lebailly, Tinne Tuytelaars
Understanding and Mitigating Memorization in Generative Models via Sharpness of Probability Landscapes
Dongjae Jeon, Dueun Kim, Albert No
TRACE Back from the Future: A Probabilistic Reasoning Approach to Controllable Language Generation
Gwen Yidou-Weng, Benjie Wang, Guy Van den Broeck
MAGELLAN: Metacognitive predictions of learning progress guide autotelic LLM agents in large goal spaces
Loris Gaven, Thomas Carta, Clément Romac et al.
Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions
Yihao Xue, Jiping Li, Baharan Mirzasoleiman
Position: Lifetime tuning is incompatible with continual reinforcement learning
Golnaz Mesbahi, Parham Mohammad Panahi, Olya Mastikhina et al.
Point-Level Topological Representation Learning on Point Clouds
Vincent P. Grande, Michael Schaub
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin S. Kang, Landon Butler, Abhineet Agarwal et al.
Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei et al.
Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss
Abhijeet Mulgund, Chirag Pabbaraju
Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF
Nuoya Xiong, Aarti Singh
Learning Dynamics in Continual Pre-Training for Large Language Models
Xingjin Wang, Howe Tissue, Lu Wang et al.
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport
Khai Nguyen, Hai Nguyen, Tuan Pham et al.
Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer
Yilun Kong, Guozheng Ma, Qi Zhao et al.
Geometric Hyena Networks for Large-scale Equivariant Learning
Artem Moskalev, Mangal Prakash, Junjie Xu et al.
Improving Multimodal Learning Balance and Sufficiency through Data Remixing
Xiaoyu Ma, Hao Chen, Yongjian Deng
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
Laixi Shi, Jingchu Gai, Eric Mazumdar et al.
Controlled Generation with Equivariant Variational Flow Matching
Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama et al.
Blink of an eye: a simple theory for feature localization in generative models
Marvin Li, Aayush Karan, Sitan Chen
SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs
Shibo Jie, Yehui Tang, Kai Han et al.
CALM: Consensus-Aware Localized Merging for Multi-Task Learning
Kunda Yan, Min Zhang, Sen Cui et al.
Nested Expectations with Kernel Quadrature
Zonghao Chen, Masha Naslidnyk, Francois-Xavier Briol
Tensor Product Neural Networks for Functional ANOVA Model
Seokhun Park, Insung Kong, yongchan Choi et al.
Sable: a Performant, Efficient and Scalable Sequence Model for MARL
Omayma Mahjoub, Sasha Abramowitz, Ruan de Kock et al.
WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction
Fanmeng Wang, Minjie Cheng, Hongteng Xu
Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport
Mingyang Sun, Pengxiang Ding, Weinan Zhang et al.
Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set
Xinyu Liu, Zixuan Xie, Shangtong Zhang
Focus On This, Not That! Steering LLMs with Adaptive Feature Specification
Tom A. Lamb, Adam Davies, Alasdair J Paren et al.
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
Tianze Wang, Dongnan Gui, Yifan Hu et al.
Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs
Faisal Hamman, Sachindra P Dissanayake, Saumitra Mishra et al.
Foundation Molecular Grammar: Multi-Modal Foundation Models Induce Interpretable Molecular Graph Languages
Michael Sun, Weize Yuan, Gang Liu et al.
Enhancing Decision-Making of Large Language Models via Actor-Critic
Heng Dong, Kefei Duan, Chongjie Zhang
Unified Breakdown Analysis for Byzantine Robust Gossip
Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx
A Theoretical Framework For Overfitting In Energy-based Modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner et al.
Gradient Boosting Reinforcement Learning
Benjamin Fuhrer, Chen Tessler, Gal Dalal
BoA: Attention-aware Post-training Quantization without Backpropagation
Junhan Kim, Ho-young Kim, Eulrang Cho et al.
SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models
Cansu Sancaktar, Christian Gumbsch, Andrii Zadaianchuk et al.
Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment
Chengting Yu, Xiaochen Zhao, Lei Liu et al.
AssistanceZero: Scalably Solving Assistance Games
Cassidy Laidlaw, Eli Bronstein, Timothy Guo et al.
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language Models
Junbo Yin, Chao Zha, Wenjia He et al.
SlimLLM: Accurate Structured Pruning for Large Language Models
Jialong Guo, Xinghao Chen, Yehui Tang et al.
Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
Harit Vishwakarma, Alan Mishler, Thomas Cook et al.
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective
Jiawei Huang, Bingcong Li, Christoph Dann et al.