Most Cited ICML "language model finetuning" Papers
5,975 papers found • Page 7 of 30
Conference
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock et al.
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barcelo, Michael Bronstein et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
Minimum Width for Universal Approximation using Squashable Activation Functions
Jonghyun Shin, Namjun Kim, Geonho Hwang et al.
Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding
Jiajun Zhu, Peihao Wang, Ruisi Cai et al.
Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
Lisha Chen, Quan Xiao, Ellen Fukuda et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He et al.
Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
Vintix: Action Model via In-Context Reinforcement Learning
Andrei Polubarov, Nikita Lyubaykin, Alexander Derevyagin et al.
Adaptive Partitioning Schemes for Optimistic Optimization
Raja Sunkara, Ardhendu Tripathy
Safety-Polarized and Prioritized Reinforcement Learning
Ke Fan, Jinpeng Zhang, Xuefeng Zhang et al.
TokenSwift: Lossless Acceleration of Ultra Long Sequence Generation
Tong Wu, Junzhe Shen, Zixia Jia et al.
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
Chi Zhang, REN Lianhai, Jingpu Cheng et al.
Unnatural Languages Are Not Bugs but Features for LLMs
Keyu Duan, Yiran Zhao, Zhili Feng et al.
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
On the Adversarial Robustness of Multi-Kernel Clustering
Hao Yu, Weixuan Liang, KE LIANG et al.
I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models
Zhenxing Mi, Kuan-Chieh Wang, Guocheng Qian et al.
Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
RISHI JINKA, Venkata Sai Mothish Gonugunta, Deepak N. Subramani
The Generalized Skew Spectrum of Graphs
Armando Bellante, Martin Plávala, Alessandro Luongo
Sample Efficient Demonstration Selection for In-Context Learning
Kiran Purohit, Venktesh V, Sourangshu Bhattacharya et al.
Unconstrained Robust Online Convex Optimization
Jiujia Zhang, Ashok Cutkosky
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Jie Wang, March Boedihardjo, Yao Xie
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
Relational Invariant Learning for Robust Solvation Free Energy Prediction
Yeyun Chen
Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
Huigen Ye, Hua Xu, An Yan et al.
When, Where and Why to Average Weights?
Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang et al.
MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
Yue Dai, Liang Liu, Xulong Tang et al.
Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang et al.
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen et al.
SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning
Jinpeng Chen, Runmin Cong, Yuzhi Zhao et al.
A Non-isotropic Time Series Diffusion Model with Moving Average Transitions
Chenxi Wang, Linxiao Yang, Zhixian Wang et al.
Novelty Detection in Reinforcement Learning with World Models
Geigh Zollicoffer, Kenneth Eaton, Jonathan Balloch et al.
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell Data
Olga Ovcharenko, Florian Barkmann, Philip Toma et al.
The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training
Matteo Saponati, Pascal J. Sager, Pau Vilimelis Aceituno et al.
The Power of Random Features and the Limits of Distribution-Free Gradient Descent
Ari Karchmer, Eran Malach
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
Georgy Noarov, Riccardo Fogliato, Martin A Bertran et al.
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
Hancheng Min, Rene Vidal
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng et al.
Position: AI Competitions Provide the Gold Standard for Empirical Rigor in GenAI Evaluation
D. Sculley, William Cukierski, Phil Culliton et al.
Understanding the Emergence of Multimodal Representation Alignment
Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin et al.
FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence
Yichen Li, Yuying Wang, Haozhao Wang et al.
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, lijiang Li et al.
Representation Preserving Multiclass Agnostic to Realizable Reduction
Steve Hanneke, Qinglin Meng, Amirreza Shaeiri
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability
Yunshu Dai, Jianwei Fei, Fangjun Huang et al.
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang et al.
Graph-Based Algorithms for Diverse Similarity Search
Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy et al.
NEAR: Neural Electromagnetic Array Response
Yinyan Bu, Jiajie Yu, Kai Zheng et al.
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
KaShun SHUM, Yuzhen Huang, Hongjian Zou et al.
Inverse Bridge Matching Distillation
Nikita Gushchin, David Li, Daniil Selikhanovych et al.
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
Yaoqin He, Junchen Fu, Kaiwen Zheng et al.
CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale
Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng et al.
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
Scaling Trends in Language Model Robustness
Nikolaus Howe, Ian McKenzie, Oskar Hollinsworth et al.
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
Marta Gentiloni Silveri, Antonio Ocello
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
Jessica Dai, Paula Gradu, Inioluwa Raji et al.
On the Importance of Gaussianizing Representations
Daniel Eftekhari, Vardan Papyan
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
Mingyu Kang, Yong Suk Choi
The Canary’s Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus, Lukas Wutschitz, Santiago Zanella-Beguelin et al.
PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design
Zhenqiao Song, Tianxiao Li, Lei Li et al.
Categorical Schrödinger Bridge Matching
Grigoriy Ksenofontov, Aleksandr Korotin
From Logits to Hierarchies: Hierarchical Clustering made Simple
Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser et al.
NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders
Jun-En Ding, Dongsheng Luo, Chenwei Wu et al.
Can Large Language Models Understand Intermediate Representations in Compilers?
Hailong Jiang, Jianfeng Zhu, Yao Wan et al.
Perceptual-GS: Scene-adaptive Perceptual Densification for Gaussian Splatting
Hongbi ZHOU, Zhangkai NI
RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing
Jinyao Guo, Chengpeng Wang, Xiangzhe Xu et al.
Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
Sayan Bhattacharya, Martín Costa, Ermiya Farokhnejad et al.
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.
On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Jaehyun Kwak, Izaaz Inhar, Se-Young Yun et al.
Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design
Vikram Kher, Manolis Zampetakis
ZipAR: Parallel Autoregressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He et al.
The Role of Sparsity for Length Generalization in LLMs
Noah Golowich, Samy Jelassi, David Brandfonbrener et al.
Text-to-LoRA: Instant Transformer Adaption
Rujikorn Charakorn, Edoardo Cetin, Yujin Tang et al.
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques
Alon Arad, Saharon Rosset
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.
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
Dachuan Shi, Yonggan Fu, Xiangchi Yuan et al.
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov et al.
Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori et al.
On the Local Complexity of Linear Regions in Deep ReLU Networks
Niket Patel, Guido Montufar
Stability and Generalization Analysis of Decentralized SGD: Sharper Bounds Beyond Lipschitzness and Smoothness
Shuang Zeng, Yunwen Lei
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Ribeiro et al.
GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen et al.
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
JINHAO LIANG, Jacob Christopher, Sven Koenig et al.
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Lee, Hojoon Kim, Yutack Park et al.
Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance
Moming Duan, Mingzhe Du, Rui Zhao et al.
Contrastive Visual Data Augmentation
Yu Zhou, Bingxuan Li, Mohan Tang et al.
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Scalable Private Partition Selection via Adaptive Weighting
Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
Patrik Reizinger, Randall Balestriero, David Klindt et al.
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He et al.
Nearly Optimal Sample Complexity for Learning with Label Proportions
Robert Busa-Fekete, Travis Dick, Claudio Gentile et al.
QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
HamidReza Imani, Jiaxin Peng, Peiman Mohseni et al.
Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
Yuhe Guo, Huayi Tang, Jiahong Ma et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Resolving Lexical Bias in Model Editing
Hammad Rizwan, Domenic Rosati, Ga Wu et al.
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama
Progressive Tempering Sampler with Diffusion
Severi Rissanen, RuiKang OuYang, Jiajun He et al.
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary Pardos et al.
Independence Tests for Language Models
Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi et al.
Field Matching: an Electrostatic Paradigm to Generate and Transfer Data
Alexander Kolesov, S. Manukhov, Vladimir Palyulin et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
Parametric Scaling Law of Tuning Bias in Conformal Prediction
Hao Zeng, Kangdao Liu, Bingyi Jing et al.
Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models
Mingjia Li, Hong Qian, Tian-Zuo Wang et al.
M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
Ziyan Wang, Zhicheng Zhang, Fei Fang et al.
Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela van der Schaar
ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning
Yuchen Lin, Ronan Le Bras, Kyle Richardson et al.
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Rickard Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj et al.
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
Graph Adaptive Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?
Wendong Zheng, Junyang Chen, Husheng Guo et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar, Vikrant Varma, David Lindner et al.
Determinant Estimation under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris van der Heide, Liam Hodgkinson et al.
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.
HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
Boyuan Li, Yicheng Luo, Zhen Liu et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.
Multimodal Medical Code Tokenizer
Xiaorui Su, Shvat Messica, Yepeng Huang et al.
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.
Understanding the difficulties of posterior predictive estimation
Abhinav Agrawal, Justin Domke
Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Muresanu, Anvith Thudi, Michael Zhang et al.
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Rethinking Benign Overfitting in Two-Layer Neural Networks
Ruichen Xu, Kexin Chen
Griffin: Towards a Graph-Centric Relational Database Foundation Model
Yanbo Wang, Xiyuan Wang, Quan Gan et al.
Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks
Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Optimizing Test-Time Compute via Meta Reinforcement Finetuning
Yuxiao Qu, Matthew Yang, Amrith Setlur et al.
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj et al.
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari et al.
Stochastic Forward–Backward Deconvolution: Training Diffusion Models with Finite Noisy Datasets
Haoye Lu, Qifan Wu, Yaoliang Yu
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
Jianting Chen
Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang et al.
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
peijie liu, Fengli Xu, Yong Li
Mind the Gap: A Practical Attack on GGUF Quantization
Kazuki Egashira, Robin Staab, Mark Vero et al.
Unlocking the Power of SAM 2 for Few-Shot Segmentation
Qianxiong Xu, Lanyun Zhu, Xuanyi Liu et al.
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci et al.
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
Yeqing Qiu, Ye XUE, Akang Wang et al.
Optimal Fair Learning Robust to Adversarial Distribution Shift
Sushant Agarwal, Amit Jayant Deshpande, Rajmohan Rajaraman et al.
Generative Audio Language Modeling with Continuous-valued Tokens and Masked Next-Token Prediction
Shu-wen Yang, Byeonggeun Kim, Kuan Po Huang et al.
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents
Shayan Kiyani, George Pappas, Aaron Roth et al.
What Has a Foundation Model Found? Inductive Bias Reveals World Models
Keyon Vafa, Peter Chang, Ashesh Rambachan et al.
Dialogue Without Limits: Constant-Sized KV Caches for Extended Response in LLMs
Ravi Ghadia, Avinash Kumar, Gaurav Jain et al.
Tree-Sliced Wasserstein Distance: A Geometric Perspective
Viet Hoang Tran, Trang Pham, Tho Tran Huu et al.
When Bad Data Leads to Good Models
Kenneth Li, Yida Chen, Fernanda Viégas et al.
Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
Simone Drago, Marco Mussi, Alberto Maria Metelli
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li, Jing Dong, Tianxing He et al.
Off-Policy Evaluation under Nonignorable Missing Data
Han Wang, Yang Xu, Wenbin Lu et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Nguyen, Chi Jin
Self-supervised Adversarial Purification for Graph Neural Networks
Woohyun Lee, Hogun Park
The Case for Learned Provenance-based System Behavior Baseline
Yao Zhu, Zhenyuan LI, yangyang wei et al.
PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
Angel Villar-Corrales, Sven Behnke
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.
KIND: Knowledge Integration and Diversion for Training Decomposable Models
Yucheng Xie, Fu Feng, Ruixiao Shi et al.
Fast Large Language Model Collaborative Decoding via Speculation
Jiale Fu, Yuchu Jiang, Junkai Chen et al.
STD-FD: Spatio-Temporal Distribution Fitting Deviation for AIGC Forgery Identification
Hengrui Lou, Zunlei Feng, Jinsong Geng et al.
Simple Policy Optimization
Zhengpeng Xie, Qiang Zhang, Fan Yang et al.
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
Blake Bordelon, Cengiz Pehlevan
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
Gen Li, Yuchen Jiao
Directly Forecasting Belief for Reinforcement Learning with Delays
Qingyuan Wu, Yuhui Wang, Simon Zhan et al.
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji et al.
TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data
Elias Chaibub Neto
Selective Preference Aggregation
Shreyas Kadekodi, Hayden McTavish, Berk Ustun
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
Chaos Meets Attention: Transformers for Large-Scale Dynamical Prediction
Yi He, Yiming Yang, Xiaoyuan Cheng et al.
DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger Bridge
Liangliang Shi, Shenhui Zhang, Xingbo Du et al.
Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion
David Geissbühler, Hatef Otroshi Shahreza, Sébastien Marcel
Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
Hanyang Zhao, Haoxian Chen, Ji Zhang et al.
Improving Diversity in Language Models: When Temperature Fails, Change the Loss
Alexandre Verine, Florian Le Bronnec, Kunhao Zheng et al.
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
Backdoor Attacks in Token Selection of Attention Mechanism
Yunjuan Wang, Raman Arora