Most Cited ICML "mean-squared error expansion" Papers
5,975 papers found • Page 10 of 30
Conference
From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium
Yi Xie, Zhanke Zhou, Chentao Cao et al.
On Temperature Scaling and Conformal Prediction of Deep Classifiers
Lahav Dabah, Tom Tirer
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.
STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
Hao Li, Qi Lv, Rui Shao et al.
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices
Jiin Woo, Laixi Shi, Gauri Joshi et al.
Loss Functions and Operators Generated by f-Divergences
Vincent Roulet, Tianlin Liu, Nino Vieillard et al.
Position: Stop Making Unscientific AGI Performance Claims
Patrick Altmeyer, Andrew Demetriou, Antony Bartlett et al.
Scalable Online Exploration via Coverability
Philip Amortila, Dylan Foster, Akshay Krishnamurthy
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
Shion Takeno, Yu Inatsu, Masayuki Karasuyama et al.
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?
Simon Park, Abhishek Panigrahi, Yun Cheng et al.
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize
Tianren Zhang, Chujie Zhao, Guanyu Chen et al.
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
Shi-ang Qi, Yakun Yu, Russell Greiner
Adaptively Perturbed Mirror Descent for Learning in Games
Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto et al.
EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
Dong HUANG, Guangtao Zeng, Jianbo Dai et al.
Contrasting Multiple Representations with the Multi-Marginal Matching Gap
Zoe Piran, Michal Klein, James Thornton et al.
FLAM: Frame-Wise Language-Audio Modeling
Yusong Wu, Christos Tsirigotis, Ke Chen et al.
An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
Emre Sahinoglu, Shahin Shahrampour
Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction
Yiting He, Zhishuai Liu, Weixin Wang et al.
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
Hongyi Peng, Han Yu, Xiaoli Tang et al.
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
Wenju Sun, Qingyong Li, Yangliao Geng et al.
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors
Emile Pierret, Bruno Galerne
Teaching Transformers Causal Reasoning through Axiomatic Training
Aniket Vashishtha, Abhinav Kumar, Atharva Pandey et al.
Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens
Ting-Ji Huang, Jia-Qi Yang, Chunxu Shen et al.
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
Graph Generative Pre-trained Transformer
Xiaohui Chen, Yinkai Wang, JIAXING HE et al.
Model-Based Minimum Bayes Risk Decoding for Text Generation
Yuu Jinnai, Tetsuro Morimura, Ukyo Honda et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
tnGPS: Discovering Unknown Tensor Network Structure Search Algorithms via Large Language Models (LLMs)
Junhua Zeng, Chao Li, Zhun Sun et al.
Ringmaster ASGD: The First Asynchronous SGD with Optimal Time Complexity
Artavazd Maranjyan, Alexander Tyurin, Peter Richtarik
Near-Optimal Sample Complexity for MDPs via Anchoring
Jongmin Lee, Mario Bravo, Roberto Cominetti
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
Alexandre Duval, Victor Schmidt, Santiago Miret et al.
Prototypical Transformer As Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun et al.
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
Haoran You, Yichao Fu, Zheng Wang et al.
Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
Jiahai Feng, Stuart Russell, Jacob Steinhardt
GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks
Shivanshu Gupta, Clemens Rosenbaum, Ethan R. Elenberg
On the Diminishing Returns of Width for Continual Learning
Etash Guha, Vihan Lakshman
Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training
Jinxia Yang, Bing Su, Xin Zhao et al.
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding
Guangyi Liu, Yu Wang, Zeyu Feng et al.
Early Time Classification with Accumulated Accuracy Gap Control
Liran Ringel, Regev Cohen, Daniel Freedman et al.
Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
Justin Lee, Behnaz Moradi-Jamei, Heman Shakeri
Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
Henry Moss, Sebastian Ober, Tom Diethe
Temporal Difference Flows
Jesse Farebrother, Matteo Pirotta, Andrea Tirinzoni et al.
SAE-V: Interpreting Multimodal Models for Enhanced Alignment
Hantao Lou, Changye Li, Jiaming Ji et al.
DriveGPT: Scaling Autoregressive Behavior Models for Driving
Xin Huang, Eric M. Wolff, Paul Vernaza et al.
Graph4MM: Weaving Multimodal Learning with Structural Information
Xuying Ning, Dongqi Fu, Tianxin Wei et al.
Generative Social Choice: The Next Generation
Niclas Boehmer, Sara Fish, Ariel Procaccia
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
Mingzhao Yang, Shangchao Su, Bin Li et al.
SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth
SafetyAnalyst: Interpretable, Transparent, and Steerable Safety Moderation for AI Behavior
Jing-Jing Li, Valentina Pyatkin, Max Kleiman-Weiner et al.
A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
Kaiwen Wang, Dawen Liang, Nathan Kallus et al.
Correlated Errors in Large Language Models
Elliot Myunghoon Kim, Avi Garg, Kenny Peng et al.
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
Shokichi Takakura, Taiji Suzuki
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
Disentangling and Integrating Relational and Sensory Information in Transformer Architectures
Awni Altabaa, John Lafferty
Step-DAD: Semi-Amortized Policy-Based Bayesian Experimental Design
Marcel Hedman, Desi Ivanova, Cong Guan et al.
Towards Compositionality in Concept Learning
Adam Stein, Aaditya Naik, Yinjun Wu et al.
Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
Yiyang Ma, Wenhan Yang, Jiaying Liu
AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models
Yaopei Zeng, Yuanpu Cao, Bochuan Cao et al.
Embedding Safety into RL: A New Take on Trust Region Methods
Nikola Milosevic, Johannes Müller, Nico Scherf
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits
Jiabin Lin, Shana Moothedath, Namrata Vaswani
Grokking in the Wild: Data Augmentation for Real-World Multi-Hop Reasoning with Transformers
Roman Abramov, Felix Steinbauer, Gjergji Kasneci
X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation
Yiwei Ma, Zhekai Lin, Jiayi Ji et al.
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
Seongho Son, William Bankes, Sayak Ray Chowdhury et al.
De-mark: Watermark Removal in Large Language Models
Ruibo Chen, Yihan Wu, Junfeng Guo et al.
Stability and Multigroup Fairness in Ranking with Uncertain Predictions
Siddartha Devic, Aleksandra Korolova, David Kempe et al.
AutoAdvExBench: Benchmarking Autonomous Exploitation of Adversarial Example Defenses
Nicholas Carlini, Edoardo Debenedetti, Javier Rando et al.
Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models
Yongxian Wei, Zixuan Hu, Li Shen et al.
Efficiently Serving Large Multimodal Models Using EPD Disaggregation
Gursimran Singh, Xinglu Wang, Yifan Hu 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
What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions
raghav singhal, Mark Goldstein, Rajesh Ranganath
Pareto Merging: Multi-Objective Optimization for Preference-Aware Model Merging
Weiyu CHEN, James Kwok
Hieros: Hierarchical Imagination on Structured State Space Sequence World Models
Paul Mattes, Rainer Schlosser, Ralf Herbrich
OpenworldAUC: Towards Unified Evaluation and Optimization for Open-world Prompt Tuning
Cong Hua, Qianqian Xu, Zhiyong Yang et al.
Scalable Model Merging with Progressive Layer-wise Distillation
Jing Xu, Jiazheng Li, Jingzhao Zhang
An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen, Dongyu Xue, Xiangxin Zhou et al.
On the Last-Iterate Convergence of Shuffling Gradient Methods
Zijian Liu, Zhengyuan Zhou
Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
Nikita Doikov, Sebastian Stich, Martin Jaggi
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian et al.
Vision-Language Models Create Cross-Modal Task Representations
Grace Luo, Trevor Darrell, Amir Bar
Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation
Junlin Han, Jianyuan Wang, Andrea Vedaldi et al.
Position: Foundation Agents as the Paradigm Shift for Decision Making
Xiaoqian Liu, Xingzhou Lou, Jianbin Jiao et al.
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
Han Wang, Sihong He, Zhili Zhang et al.
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Shu Heng Yeo, Axel Carlier et al.
Stereo Risk: A Continuous Modeling Approach to Stereo Matching
Ce Liu, Suryansh Kumar, Shuhang Gu et al.
XAttnMark: Learning Robust Audio Watermarking with Cross-Attention
Yixin Liu, Lie Lu, Jihui Jin et al.
Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
Yujin Han, Andi Han, Wei Huang et al.
Nesting Particle Filters for Experimental Design in Dynamical Systems
Sahel Iqbal, Adrien Corenflos, Simo Särkkä et al.
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan et al.
Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective
Zeyu Jia, Alexander Rakhlin, Tengyang Xie
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
Chendi Wang, Yuqing Zhu, Weijie Su et al.
Understanding High-Dimensional Bayesian Optimization
Leonard Papenmeier, Matthias Poloczek, Luigi Nardi
Initial Guessing Bias: How Untrained Networks Favor Some Classes
Emanuele Francazi, Aurelien Lucchi, Marco Baity-Jesi
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
Hui Dai, Ryan Teehan, Mengye Ren
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
Kunal Jha, Wilka Carvalho, Yancheng Liang et al.
Risk and cross validation in ridge regression with correlated samples
Alexander Atanasov, Jacob A Zavatone-Veth, Cengiz Pehlevan
When Representations Align: Universality in Representation Learning Dynamics
Loek van Rossem, Andrew Saxe
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Luca Viano, EFSTRATIOS PANTELEIMON SKOULAKIS, Volkan Cevher
EgoPrivacy: What Your First-Person Camera Says About You?
Yijiang Li, Genpei Zhang, Jiacheng Cheng et al.
Kernel Semi-Implicit Variational Inference
Ziheng Cheng, Longlin Yu, Tianyu Xie et al.
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
Rudy Morel, Jiequn Han, Edouard Oyallon
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
Noa Rubin, Kirsten Fischer, Javed Lindner et al.
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang et al.
Hierarchical Graph Tokenization for Molecule-Language Alignment
Yongqiang Chen, QUANMING YAO, Juzheng Zhang et al.
Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation
Jingyu Liu, Beidi Chen, Ce Zhang
Latent Diffusion Planning for Imitation Learning
Amber Xie, Oleh Rybkin, Dorsa Sadigh et al.
Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models
Minh-Tung Luu, Younghwan Lee, Donghoon Lee et al.
A General Framework for Learning from Weak Supervision
Hao Chen, Jindong Wang, Lei Feng et al.
LOGO --- Long cOntext aliGnment via efficient preference Optimization
Zecheng Tang, Zechen Sun, Juntao Li et al.
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
guangyan li, Yongqiang Tang, Wensheng Zhang
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao et al.
EvIL: Evolution Strategies for Generalisable Imitation Learning
Silvia Sapora, Gokul Swamy, Christopher Lu et al.
Impossible Videos
Zechen Bai, Hai Ci, Mike Zheng Shou
Does learning the right latent variables necessarily improve in-context learning?
Sarthak Mittal, Eric Elmoznino, Léo Gagnon et al.
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, JIAMING LIU, Edward Chandler et al.
SMaRt: Improving GANs with Score Matching Regularity
Mengfei Xia, Yujun Shen, Ceyuan Yang et al.
Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation
Shuanghao Bai, Wanqi Zhou, Pengxiang Ding et al.
Adaptive kernel predictors from feature-learning infinite limits of neural networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
Eluder-based Regret for Stochastic Contextual MDPs
Orin Levy, Asaf Cassel, Alon Cohen et al.
Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
Yuantong Li, Guang Cheng, Xiaowu Dai
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovic
Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples
Fangxu Yu, Lai Jiang, Haoqiang Kang et al.
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai et al.
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu
Random Latent Exploration for Deep Reinforcement Learning
Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari et al.
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
Zheng Huang, Qihui Yang, Dawei Zhou et al.
Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence
Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi et al.
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
Fanchen Bu, Hyeonsoo Jo, Soo Yong Lee et al.
PROXSPARSE: REGULARIZED LEARNING OF SEMI-STRUCTURED SPARSITY MASKS FOR PRETRAINED LLMS
Hongyi Liu, Rajarshi Saha, Zhen Jia et al.
Mechanisms of Projective Composition of Diffusion Models
Arwen Bradley, Preetum Nakkiran, David Berthelot et al.
Semantically-correlated memories in a dense associative model
Thomas F Burns
Few-Shot Learner Generalizes Across AI-Generated Image Detection
Shiyu Wu, Jing Liu, Jing Li et al.
On dimensionality of feature vectors in MPNNs
César Bravo, Alexander Kozachinskiy, Cristobal Rojas
3D Geometric Shape Assembly via Efficient Point Cloud Matching
Nahyuk Lee, Juhong Min, Junha Lee et al.
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Beguelin et al.
Toward Robust Hyper-Detailed Image Captioning: A Multiagent Approach and Dual Evaluation Metrics for Factuality and Coverage
Saehyung Lee, Seunghyun Yoon, Trung Bui et al.
UDora: A Unified Red Teaming Framework against LLM Agents by Dynamically Hijacking Their Own Reasoning
Jiawei Zhang, Shuang Yang, Bo Li
A fast algorithm to simulate nonlinear resistive networks
Benjamin Scellier
Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models
Mingi Jung, Saehyung Lee, Eunji Kim et al.
xT: Nested Tokenization for Larger Context in Large Images
Ritwik Gupta, Shufan Li, Tyler Zhu et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Nguyen, Chi Jin
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
Aleksandr Beznosikov, David Dobre, Gauthier Gidel
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Rectifying Conformity Scores for Better Conditional Coverage
Vincent Plassier, Alexander Fishkov, Victor Dheur et al.
Generative Active Learning for Long-tailed Instance Segmentation
Muzhi Zhu, Chengxiang Fan, Hao Chen et al.
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice
Masahiro Kato, Oga Akihiro, Wataru Komatsubara et al.
Progressive Tempering Sampler with Diffusion
Severi Rissanen, RuiKang OuYang, Jiajun He et al.
Federated Combinatorial Multi-Agent Multi-Armed Bandits
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
Griffin: Towards a Graph-Centric Relational Database Foundation Model
Yanbo Wang, Xiyuan Wang, Quan Gan et al.
Bayesian Optimization of Function Networks with Partial Evaluations
Poompol Buathong, Jiayue Wan, Raul Astudillo et al.
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li, Jing Dong, Tianxing He et al.
GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation
Mengzhu Wang, houcheng su, Jiao Li et al.
Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion
Ishaan Rawal, Alexander Matyasko, Shantanu Jaiswal et al.
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
Vithursan Thangarasa, Shreyas Saxena, Abhay Gupta et al.
What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement
Xisen Jin, Xiang Ren
How Do Transformers Learn Variable Binding in Symbolic Programs?
Yiwei Wu, Atticus Geiger, Raphaël Millière
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang et al.
Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications
Maria Despoina Siampou, Jialiang Li, John Krumm et al.
Self-Discriminative Modeling for Anomalous Graph Detection
Jinyu Cai, Yunhe Zhang, Jicong Fan
Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization
Zelai Xu, Wanjun Gu, Chao Yu et al.
GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity Extrapolation
Jiashu HE, Mingyu Ma, Jinxuan Fan et al.
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
Yike Yuan, Ziyu Wang, Zihao Huang et al.
Unified Breakdown Analysis for Byzantine Robust Gossip
Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
Ossi Räisä, Joonas Jälkö, Antti Honkela
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou
Combinatorial Multivariant Multi-Armed Bandits with Applications to Episodic Reinforcement Learning and Beyond
Xutong Liu, Siwei Wang, Jinhang Zuo et al.
Understanding MLP-Mixer as a wide and sparse MLP
Tomohiro Hayase, Ryo Karakida
Model-based Reinforcement Learning for Parameterized Action Spaces
Renhao Zhang, Haotian Fu, Yilin Miao et al.
GaussMark: A Practical Approach for Structural Watermarking of Language Models
Adam Block, Alexander Rakhlin, Ayush Sekhari
Transferring Knowledge From Large Foundation Models to Small Downstream Models
Shikai Qiu, Boran Han, Danielle Robinson et al.
Perception in Reflection
Yana Wei, Liang Zhao, Kangheng Lin et al.
Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method
Jeeveswaran Kishaan, Elahe Arani, Bahram Zonooz
Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.
Adaptive Conformal Inference by Betting
Aleksandr Podkopaev, Darren Xu, Kuang-chih Lee
Towards a Better Theoretical Understanding of Independent Subnetwork Training
Egor Shulgin, Peter Richtarik
Meta-Black-Box-Optimization through Offline Q-function Learning
Zeyuan Ma, Zhiguang Cao, Zhou Jiang et al.
Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
Chenbei Lu, Laixi Shi, Zaiwei Chen et al.
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning
Thomas T. Zhang, Behrad Moniri, Ansh Nagwekar et al.
Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data
Haitong LIU, Qiang Li, Hoi To Wai
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers
Duo Peng, Qiuhong Ke, Jun Liu
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
Pei Liu, Luping Ji
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang, Niao He, Andreas Krause
Total Variation Distance Meets Probabilistic Inference
Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel et al.
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen et al.
Representative Language Generation
Charlotte Peale, Vinod Raman, Omer Reingold
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong
Volume Optimality in Conformal Prediction with Structured Prediction Sets
Chao Gao, Liren Shan, Vaidehi Srinivas et al.
Geometry-Informed Neural Networks
Arturs Berzins, Andreas Radler, Eric Volkmann 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.
Benchmarking Quantum Reinforcement Learning
Nico Meyer, Christian Ufrecht, George Yammine et al.
Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Qinglin Zhu, Runcong Zhao, Hanqi Yan et al.
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
Collage: Light-Weight Low-Precision Strategy for LLM Training
Tao Yu, Gaurav Gupta, KARTHICK GOPALSWAMY et al.
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Qinzi Zhang, Ashok Cutkosky
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent
Yingru Li, Jiawei Xu, Lei Han et al.
The Perception-Robustness Tradeoff in Deterministic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity
Chang He, Zhaoye Pan, Xiao Wang et al.