Most Cited ICML "language model finetuning" Papers
5,975 papers found • Page 14 of 30
Conference
HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs
Mingquan Feng, Weixin Liao, Yixin Huang et al.
Activation-Descent Regularization for Input Optimization of ReLU Networks
Hongzhan Yu, Sicun Gao
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
Ziao Guo, Yang Li, Chang Liu et al.
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Le Yu, Bowen Yu, Haiyang Yu et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators
Jianhao Yuan, Francesco Pinto, Adam Davies et al.
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
AI Control: Improving Safety Despite Intentional Subversion
Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
Robust Learning-Augmented Dictionaries
Ali Zeynali, Shahin Kamali, Mohammad Hajiesmaili
Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders
Zhiheng Zhang
DAG-Based Column Generation for Adversarial Team Games
Youzhi Zhang, Bo An, Daniel Zeng
Evolution-Inspired Loss Functions for Protein Representation Learning
Chengyue Gong, Adam Klivans, James Loy et al.
Self-Correcting Self-Consuming Loops for Generative Model Training
Nate Gillman, Michael Freeman, Daksh Aggarwal et al.
Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
Avishek Ghosh, Arya Mazumdar
Random Scaling and Momentum for Non-smooth Non-convex Optimization
Qinzi Zhang, Ashok Cutkosky
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde
ILILT: Implicit Learning of Inverse Lithography Technologies
Haoyu Yang, Mark Ren
Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment
Chen Zhang, Qiang HE, Yuan Zhou et al.
Deep Regression Representation Learning with Topology
Shihao Zhang, Kenji Kawaguchi, Angela Yao
DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts
Tobias Braun, Mark Rothermel, Marcus Rohrbach et al.
UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.
Adaptive Exploration for Multi-Reward Multi-Policy Evaluation
Alessio Russo, Aldo Pacchiano
Nonparametric Teaching of Implicit Neural Representations
Chen Zhang, Steven T. S. Luo, Jason Chun Lok Li et al.
State-Constrained Zero-Sum Differential Games with One-Sided Information
Mukesh Ghimire, Lei Zhang, Zhe Xu et al.
Switchable Decision: Dynamic Neural Generation Networks
Shujian Zhang, Korawat Tanwisuth, Chengyue Gong et al.
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective
Yulong Zhang, Yuan Yao, Shuhao Chen et al.
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
Yu Zhang, Qi Zhang, Zixuan Gong et al.
Safe and Robust Subgame Exploitation in Imperfect Information Games
Zhenxing Ge, Zheng Xu, Tianyu Ding et al.
Neural Jump-Diffusion Temporal Point Processes
Shuai Zhang, Chuan Zhou, Yang Liu et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation
Zhihao Zhang, Alan Zhu, Lijie Yang et al.
Rethinking Score Distilling Sampling for 3D Editing and Generation
Xingyu Miao, Haoran Duan, Yang Long et al.
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
Chenxu Zhao, Wei Qian, Yangyi Li et al.
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.
Double-Step Alternating Extragradient with Increasing Timescale Separation for Finding Local Minimax Points: Provable Improvements
Kyuwon Kim, Donghwan Kim
LLark: A Multimodal Instruction-Following Language Model for Music
Josh Gardner, Simon Durand, Daniel Stoller et al.
LangCell: Language-Cell Pre-training for Cell Identity Understanding
Suyuan Zhao, Jiahuan Zhang, Yushuai Wu et al.
Projection-Free Online Convex Optimization with Time-Varying Constraints
Dan Garber, Ben Kretzu
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, ZHIMING ZHANG, Shu Yang
Upcycling Text-to-Image Diffusion Models for Multi-Task Capabilities
Ruchika Chavhan, Abhinav Mehrotra, Malcolm Chadwick et al.
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, xiyao wang et al.
Implicit degree bias in the link prediction task
Rachith Aiyappa, Xin Wang, Munjung Kim et al.
Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
Wenzhi Gao, Chunlin Sun, Chenyu Xue et al.
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
Feng Gao, Liangzhi Shi, Shenao Zhang et al.
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers
Yunshan Zhong, Jiawei Hu, You Huang et al.
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
Bowen Gao, Minsi Ren, Yuyan Ni et al.
GNNs Also Deserve Editing, and They Need It More Than Once
Shaochen (Henry) Zhong, Duy Le, Zirui Liu et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
Pedestrian Attribute Recognition as Label-balanced Multi-label Learning
Yibo Zhou, Hai-Miao Hu, Yirong Xiang et al.
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting
Xiaoyu Zhou, Xingjian Ran, Yajiao Xiong et al.
Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process
Xiangxin Zhou, Liang Wang, Yichi Zhou
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet et al.
Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang et al.
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Iterative Search Attribution for Deep Neural Networks
Zhiyu Zhu, Huaming Chen, Xinyi Wang et al.
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao, Daize Dong, Cheng Tan et al.
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong et al.
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao et al.
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama et al.
Stealthy Imitation: Reward-guided Environment-free Policy Stealing
Zhixiong Zhuang, Irina Nicolae, Mario Fritz
Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal et al.
Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration
Zhengyang Zhuge, Peisong Wang, Xingting Yao et al.
Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Li, Rohith Kuditipudi et al.
BiE: Bi-Exponent Block Floating-Point for Large Language Models Quantization
Lancheng Zou, Wenqian Zhao, Shuo Yin et al.
Reflective Policy Optimization
Yaozhong Gan, yan renye, zhe wu et al.
Exploration and Anti-Exploration with Distributional Random Network Distillation
Kai Yang, jian tao, Jiafei Lyu et al.
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data
Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng et al.
Revisiting Character-level Adversarial Attacks for Language Models
Elias Abad Rocamora, Yongtao Wu, Fanghui Liu et al.
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
Yechan Kim, Hwijoon Lim, Dongsu Han
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
COPAL: Continual Pruning in Large Language Generative Models
Srikanth Malla, Joon Hee Choi, Chiho Choi
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna Ballard, Mohan Zhang et al.
Multimodal Prototyping for cancer survival prediction
Andrew Song, Richard Chen, Guillaume Jaume et al.
A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
Shentao Yang, Tianqi Chen, Mingyuan Zhou
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu, Sen Zhang, Yingjie Wang et al.
UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
Xi Han, Fei Hou, Hong Qin
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation
Han Fu, Jian Tan, Pinhan Zhang et al.
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
Knowledge-aware Reinforced Language Models for Protein Directed Evolution
Yuhao Wang, Qiang Zhang, Ming Qin et al.
Hyperbolic Geometric Latent Diffusion Model for Graph Generation
Xingcheng Fu, Yisen Gao, Yuecen Wei et al.
DNCs Require More Planning Steps
Yara Shamshoum, Nitzan Hodos, Yuval Sieradzki et al.
Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi et al.
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
Flow Matching for Denoised Social Recommendation
Yinxuan Huang, KE LIANG, Zhuofan Dong et al.
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
Yididiya Nadew, Xuhui Fan, Christopher J Quinn
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Ignat Georgiev, Krishnan Srinivasan, Jie Xu et al.
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Low-Rank Similarity Mining for Multimodal Dataset Distillation
Yue Xu, Zhilin Lin, Yusong Qiu et al.
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Tom Fischer, Pascal Peter, Joachim Weickert et al.
Compositional Text-to-Image Generation with Dense Blob Representations
Weili Nie, Sifei Liu, Morteza Mardani et al.
Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding
Chuanhao Sun, Zhihang Yuan, Kai Xu et al.
A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
Kai Weixian Lan, Elias Gueidon, Ayano Kaneda et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
Yair Schiff, Zhong Yi Wan, Jeffrey Parker et al.
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.
BAT: Learning to Reason about Spatial Sounds with Large Language Models
Zhisheng Zheng, Puyuan Peng, Ziyang Ma et al.
From Biased Selective Labels to Pseudo-Labels: An Expectation-Maximization Framework for Learning from Biased Decisions
Trenton Chang, Jenna Wiens
How Does Goal Relabeling Improve Sample Efficiency?
Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.
Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling
Zehao Dou, Minshuo Chen, Mengdi Wang et al.
Enhancing Adversarial Robustness in SNNs with Sparse Gradients
Yujia Liu, Tong Bu, Ding Jianhao et al.
Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen et al.
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song et al.
EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
Chung-Yiu Yau, Hoi To Wai, Parameswaran Raman et al.
Smoothness Adaptive Hypothesis Transfer Learning
Haotian Lin, Matthew Reimherr
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier et al.
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu et al.
NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors
Shi-Sheng Huang, Guo Chen, Li-heng Chen et al.
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
Yukinari Hisaki, Isao Ono
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Yongxian Wei, Anke Tang, Li Shen et al.
Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations
Ze Cheng, Zhongkai Hao, Wang Xiaoqiang et al.
Learning from Sample Stability for Deep Clustering
Zhixin Li, Yuheng Jia, Hui LIU et al.
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
Jianliang He, Siyu Chen, Fengzhuo Zhang et al.
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra
Alan Amin, Andres Potapczynski, Andrew Wilson
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
Guanhua Zhang, Moritz Hardt
On the Minimal Degree Bias in Generalization on the Unseen for non-Boolean Functions
Denys Pushkin, Raphaël Berthier, Emmanuel Abbe
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou, Shuanghao Bai, Shujian Yu et al.
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
Christophe Vauthier, Anna Korba, Quentin Mérigot
Energy-based Backdoor Defense without Task-Specific Samples and Model Retraining
Yudong Gao, Honglong Chen, Peng Sun et al.
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng, Aayush Jain, David Woodruff
Causal Inference from Competing Treatments
Ana-Andreea Stoica, Vivian Y. Nastl, Moritz Hardt
Denoising Autoregressive Representation Learning
Yazhe Li, Jorg Bornschein, Ting Chen
On a Neural Implementation of Brenier's Polar Factorization
Nina Vesseron, Marco Cuturi
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji et al.
Privacy Attacks in Decentralized Learning
Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Hybrid Neural Representations for Spherical Data
Hyomin Kim, Yunhui Jang, Jaeho Lee et al.
Mastering Zero-Shot Interactions in Cooperative and Competitive Simultaneous Games
Yannik Mahlau, Frederik Schubert, Bodo Rosenhahn
SparQ Attention: Bandwidth-Efficient LLM Inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley et al.
Adaptive Stabilization Based on Machine Learning for Column Generation
Yunzhuang Shen, Yuan Sun, Xiaodong Li et al.
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective
Fabian Falck, Ziyu Wang, Christopher Holmes
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
Leveraging VLM-Based Pipelines to Annotate 3D Objects
Rishabh Kabra, Loic Matthey, Alexander Lerchner et al.
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras et al.
PEARL: Zero-shot Cross-task Preference Alignment and Robust Reward Learning for Robotic Manipulation
Runze Liu, Yali Du, Fengshuo Bai et al.
Compositional Curvature Bounds for Deep Neural Networks
Taha Entesari, Sina Sharifi, Mahyar Fazlyab
Ai-sampler: Adversarial Learning of Markov kernels with involutive maps
Evgenii Egorov, Riccardo Valperga, Efstratios Gavves
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
RoboDreamer: Learning Compositional World Models for Robot Imagination
Siyuan Zhou, Yilun Du, Jiaben Chen et al.
3D-VLA: A 3D Vision-Language-Action Generative World Model
Haoyu Zhen, Xiaowen Qiu, Peihao Chen et al.
Approximate Nearest Neighbor Search with Window Filters
Josh Engels, Ben Landrum, Shangdi Yu et al.
Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials
Jonathan Scott, Aine E Cahill
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
Time Series Diffusion in the Frequency Domain
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk et al.
Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller, Marius Zeinhofer
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Trained Random Forests Completely Reveal your Dataset
Julien Ferry, Ricardo Fukasawa, Timothée Pascal et al.
PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
Xinghe Fu, Zhiyuan Yan, Zheng Yang et al.
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed Zaki, Dharmashankar Subramanian
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff et al.
Verification of Machine Unlearning is Fragile
Binchi Zhang, Zihan Chen, Cong Shen et al.
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
Benjamin Dupuis, Umut Simsekli
Dirichlet Flow Matching with Applications to DNA Sequence Design
Hannes Stärk, Bowen Jing, Chenyu Wang et al.
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre la Tour, Monika Henzinger, David Saulpic
Listenable Maps for Audio Classifiers
Francesco Paissan, Mirco Ravanelli, Cem Subakan
Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
Hiren Madhu, Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
Regularized Q-learning through Robust Averaging
Peter Schmitt-Förster, Tobias Sutter
Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling
Weijia Xu, Andrzej Banburski-Fahey, Nebojsa Jojic
Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation
Yudan Wang, Yue Wang, Yi Zhou et al.
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
Florian Tramer, Gautam Kamath, Nicholas Carlini
Differentially Private Post-Processing for Fair Regression
Ruicheng Xian, Qiaobo Li, Gautam Kamath et al.
Position: Automatic Environment Shaping is the Next Frontier in RL
Younghyo Park, Gabriel Margolis, Pulkit Agrawal
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning
Hongye Jin, Xiaotian Han, Jingfeng Yang et al.
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Dung, Cuong Pham, Trung Le et al.
Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning
Vivienne Wang, Tinghuai Wang, wenyan yang et al.
DE-COP: Detecting Copyrighted Content in Language Models Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Ryan Liu, Theodore R Sumers, Ishita Dasgupta et al.
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu et al.
Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
Ingvar Ziemann, Stephen Tu, George Pappas et al.
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
YU DU, Fangyun Wei, Hongyang Zhang
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert et al.
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Sharon Li
AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
Junkang Wu, xue wang, Zhengyi Yang et al.
Fully Dynamic Embedding into $\ell_p$ Spaces
Kiarash Banihashem, Xiang Chen, MohammadTaghi Hajiaghayi et al.
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
Konstantin Donhauser, Javier Abad, Neha Hulkund et al.
Differentially Private Federated $k$-Means Clustering with Server-Side Data
Jonathan Scott, Christoph Lampert, David Saulpic
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
Harry Dong, Xinyu Yang, Zhenyu Zhang et al.
Accelerating PDE Data Generation via Differential Operator Action in Solution Space
huanshuo dong, Hong Wang, Haoyang Liu et al.
Fully Heteroscedastic Count Regression with Deep Double Poisson Networks
Spencer Young, Porter Jenkins, Longchao Da et al.