Most Cited ICML "decision boundary mapping" Papers
5,975 papers found • Page 11 of 30
Conference
Online Non-stochastic Control with Partial Feedback
Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
Zhuowen Yuan, Zidi Xiong, Yi Zeng et al.
Understanding the Learning Dynamics of Alignment with Human Feedback
Shawn Im, Sharon Li
CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
Kaiyuan Chen, Xingzhuo Guo, Yu Zhang et al.
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan et al.
Recovering Labels from Local Updates in Federated Learning
Huancheng Chen, Haris Vikalo
Smooth Min-Max Monotonic Networks
Christian Igel
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
Runfa Chen, Ling Wang, Yu Du et al.
A General Framework for Learning from Weak Supervision
Hao Chen, Jindong Wang, Lei Feng et al.
Diffusion Model-Augmented Behavioral Cloning
Shang-Fu Chen, Hsiang-Chun Wang, Ming-Hao Hsu et al.
Make-A-Shape: a Ten-Million-scale 3D Shape Model
Ka-Hei Hui, Aditya Sanghi, Arianna Rampini et al.
Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
Anthony Chen, Huanrui Yang, Yulu Gan et al.
The Underlying Universal Statistical Structure of Natural Datasets
Noam Levi, Yaron Oz
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe et al.
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
Diffusive Gibbs Sampling
Wenlin Chen, Mingtian Zhang, Brooks Paige et al.
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
Zelei Cheng, Xian Wu, Jiahao Yu et al.
Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence
Yancheng Huang, Kai Yang, Zelin Zhu et al.
Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
Wang Chi Cheung, Lixing Lyu
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
Quasi-Monte Carlo Features for Kernel Approximation
ZHEN HUANG, Jiajin Sun, Yian Huang
Neurodegenerative Brain Network Classification via Adaptive Diffusion with Temporal Regularization
Hyuna Cho, Jaeyoon Sim, Guorong Wu et al.
MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution
Shuying Huang, Mingyang Ren, Yong Yang et al.
Online bipartite matching with imperfect advice
Davin Choo, Themis Gouleakis, Chun Kai Ling et al.
Prompt-tuning Latent Diffusion Models for Inverse Problems
Hyungjin Chung, Jong Chul YE, Peyman Milanfar et al.
$\mathtt{VITS}$ : Variational Inference Thompson Sampling for contextual bandits
Pierre Clavier, Tom Huix, Alain Oliviero Durmus
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng LIN, Hongwei Ren et al.
Weighted distance nearest neighbor condensing
Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant et al.
Statistical Inference Under Constrained Selection Bias
Santiago Cortes-Gomez, Mateo Dulce Rubio, Carlos Miguel Patiño et al.
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games
Kexin Huang, Ziqian Chen, xue wang et al.
Harmonizing Generalization and Personalization in Federated Prompt Learning
Tianyu Cui, Hongxia Li, Jingya Wang et al.
ReconBoost: Boosting Can Achieve Modality Reconcilement
Cong Hua, Qianqian Xu, Shilong Bao et al.
Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation
Juntao Dai, Yaodong Yang, Qian Zheng et al.
Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications
Zixuan Hu, Yongxian Wei, Li Shen et al.
New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering
Sanjoy Dasgupta, Eduardo Laber
Provable Privacy with Non-Private Pre-Processing
Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf
Provably Better Explanations with Optimized Aggregation of Feature Attributions
Thomas Decker, Ananta Bhattarai, Jindong Gu et al.
An Information Theoretic Approach to Interaction-Grounded Learning
Xiaoyan Hu, Farzan Farnia, Ho-fung Leung
Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing
VIKAS DEEP, Achal Bassamboo, Sandeep Juneja
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
Collaborative Learning with Different Labeling Functions
yuyang deng, Mingda Qiao
Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
Yusong Hu, De Cheng, Dingwen Zhang et al.
Towards Memorization Estimation: Fast, Formal and Free
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs
Kihyuk Hong, Ambuj Tewari
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin et al.
Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding
Dianwen Ng, Kun Zhou, Yi-Wen Chao et al.
Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts
Jiahai Feng, Stuart Russell, Jacob Steinhardt
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma et al.
Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
Zhiyuan He, Yijun Yang, Pin-Yu Chen et al.
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre et al.
Quantum Algorithm for Online Exp-concave Optimization
Jianhao He, Chengchang Liu, Xutong Liu et al.
Deep Neural Room Acoustics Primitive
Yuhang He, Anoop Cherian, Gordon Wichern et al.
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
Haozhao Wang, Shengyu Wang, Jiaming Li et al.
Revolve: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization
Peiyan Zhang, Haibo Jin, Leyang Hu et al.
Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia et al.
MGit: A Model Versioning and Management System
Wei Hao, Daniel Mendoza, Rafael Mendes et al.
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce et al.
Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
Jan Hagnberger, Marimuthu Kalimuthu, Daniel Musekamp et al.
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
Zijian Guo, Weichao Zhou, Wenchao Li
Compressing Large Language Models by Joint Sparsification and Quantization
Jinyang Guo, Jianyu Wu, Zining Wang et al.
HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs
Mingquan Feng, Weixin Liao, Yixin Huang et al.
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
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
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde
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
Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization
Badih Ghazi, Pritish Kamath, Ravi Kumar et al.
Positive-unlabeled AUC Maximization under Covariate Shift
Atsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi et al.
Rethinking Score Distilling Sampling for 3D Editing and Generation
Xingyu Miao, Haoran Duan, Yang Long et al.
LLark: A Multimodal Instruction-Following Language Model for Music
Josh Gardner, Simon Durand, Daniel Stoller et al.
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.
Implicit degree bias in the link prediction task
Rachith Aiyappa, Xin Wang, Munjung Kim et al.
Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
Feng Gao, Liangzhi Shi, Shenao Zhang et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet et al.
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao, Daize Dong, Cheng Tan et al.
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama et al.
Reinforcement Learning with Segment Feedback
Yihan Du, Anna Winnicki, Gal Dalal et al.
Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Li, Rohith Kuditipudi et al.
Reflective Policy Optimization
Yaozhong Gan, yan renye, zhe wu et al.
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion
Bowen Gao, Minsi Ren, Yuyan Ni et al.
$\texttt{I$^2$MoE}$: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng 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.
Let Go of Your Labels with Unsupervised Transfer
Artyom Gadetsky, Yulun Jiang, Maria Brbic
Projection-Free Online Convex Optimization with Time-Varying Constraints
Dan Garber, Ben Kretzu
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.
Safe and Robust Subgame Exploitation in Imperfect Information Games
Zhenxing Ge, Zheng Xu, Tianyu Ding et al.
Learning with 3D rotations, a hitchhiker's guide to SO(3)
Andreas René Geist, Jonas Frey, Mikel Zhobro et al.
Modalities Contribute Unequally: Enhancing Medical Multi-modal Learning through Adaptive Modality Token Re-balancing
Jie Peng, Jenna Ballard, Mohan Zhang et al.
State-Constrained Zero-Sum Differential Games with One-Sided Information
Mukesh Ghimire, Lei Zhang, Zhe Xu et al.
Towards Theoretical Understandings of Self-Consuming Generative Models
Shi Fu, Sen Zhang, Yingjie Wang et al.
PinNet: Pinpoint Instructive Information for Retrieval Augmented Code-to-Text Generation
Han Fu, Jian Tan, Pinhan Zhang et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
Hyperbolic Geometric Latent Diffusion Model for Graph Generation
Xingcheng Fu, Yisen Gao, Yuecen Wei et al.
Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning
Wenke Huang, Jian Liang, Zekun Shi et al.
AI Control: Improving Safety Despite Intentional Subversion
Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan et al.
Predictive Performance Comparison of Decision Policies Under Confounding
Luke Guerdan, Amanda Coston, Ken Holstein et al.
ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation
Ziao Guo, Yang Li, Chang Liu et al.
Flow Matching for Denoised Social Recommendation
Yinxuan Huang, KE LIANG, Zhuofan Dong et al.
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Inverse-Variance Weighting for Estimation of Heterogeneous Treatment Effects
Aaron Fisher
Prototypical Transformer As Unified Motion Learners
Cheng Han, Yawen Lu, Guohao Sun et al.
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Tom Fischer, Pascal Peter, Joachim Weickert et al.
Estimating the Permanent by Nesting Importance Sampling
Juha Harviainen, Mikko Koivisto
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformer
Doron Haviv, Russell Kunes, Thomas Dougherty et al.
GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements
Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation
Nantian He, Shaohui Li, Zhi Li et al.
Demeaned Sparse: Efficient Anomaly Detection by Residual Estimate
Yifan Fang, Yifei Fang, Ruizhe Chen et al.
Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity
Chang He, Zhaoye Pan, Xiao Wang et al.
Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
Thomas Ferté, Dutartre Dan, Boris Hejblum et al.
Robust Multi-Task Learning with Excess Risks
Yifei He, Shiji Zhou, Guojun Zhang et al.
Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates
Rémi Leluc, Aymeric Dieuleveut, François Portier et al.
Learning Useful Representations of Recurrent Neural Network Weight Matrices
Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber
Randomized Confidence Bounds for Stochastic Partial Monitoring
Maxime Heuillet, Ola Ahmad, Audrey Durand
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
Minh Hoang, Azza Fadhel, Aryan Deshwal et al.
TAROT: Targeted Data Selection via Optimal Transport
Lan Feng, Fan Nie, Yuejiang Liu et al.
Enhancing Sufficient Dimension Reduction via Hellinger Correlation
Seungbeom Hong, Ilmun Kim, Jun Song
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency
Linshan Hou, Ruili Feng, Zhongyun Hua et al.
Loss Shaping Constraints for Long-Term Time Series Forecasting
Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Yongxian Wei, Anke Tang, Li Shen et al.
Learning from Sample Stability for Deep Clustering
Zhixin Li, Yuheng Jia, Hui LIU et al.
Case-Based or Rule-Based: How Do Transformers Do the Math?
Yi Hu, Xiaojuan Tang, Haotong Yang et al.
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra
Alan Amin, Andres Potapczynski, Andrew Wilson
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
Christophe Vauthier, Anna Korba, Quentin Mérigot
Fast White-Box Adversarial Streaming Without a Random Oracle
Ying Feng, Aayush Jain, David Woodruff
Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
Jiawei Huang, Niao He, Andreas Krause
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji et al.
INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
Han Fang, Zhihao Song, Paul Weng et al.
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras et al.
Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
Compositional Curvature Bounds for Deep Neural Networks
Taha Entesari, Sina Sharifi, Mahyar Fazlyab
An Embodied Generalist Agent in 3D World
Jiangyong Huang, Silong Yong, Xiaojian Ma et al.
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning
Joon Suk Huh, Kirthevasan Kandasamy
Approximate Nearest Neighbor Search with Window Filters
Josh Engels, Ben Landrum, Shangdi Yu et al.
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Hellsten, Luigi Nardi
Position: Insights from Survey Methodology can Improve Training Data
Stephanie Eckman, Barbara Plank, Frauke Kreuter
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Zero-Shot Reinforcement Learning via Function Encoders
Tyler Ingebrand, Amy Zhang, Ufuk Topcu
PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
Xinghe Fu, Zhiyuan Yan, Zheng Yang et al.
Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alex Shestopaloff et al.
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation
Benjamin Dupuis, Umut Simsekli
Making Old Things New: A Unified Algorithm for Differentially Private Clustering
Max Dupre la Tour, Monika Henzinger, David Saulpic
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
Tianying Ji, Yongyuan Liang, Yan Zeng et al.
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han et al.
Generalized Neural Collapse for a Large Number of Classes
Jiachen Jiang, Jinxin Zhou, Peng Wang et al.
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
Shibo Jie, Yehui Tang, Ning Ding et al.
Homomorphism Counts for Graph Neural Networks: All About That Basis
Emily Jin, Michael Bronstein, Ismail Ceylan et al.
Sharpness-Aware Data Generation for Zero-shot Quantization
Hoang Dung, Cuong Pham, Trung Le et al.
DE-COP: Detecting Copyrighted Content in Language Models Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu et al.
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott Jordan, Adam White, Bruno da Silva et al.
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
YU DU, Fangyun Wei, Hongyang Zhang
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy
Georgios Kaissis, Stefan Kolek, Borja de Balle Pigem et al.
C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models
Mintong Kang, Nezihe Merve Gürel, Ning Yu et al.
Think Before You Act: Decision Transformers with Working Memory
Jikun Kang, Romain Laroche, Xingdi Yuan 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.
Pluvial Flood Emulation with Hydraulics-informed Message Passing
Arnold Kazadi, James Doss-Gollin, Arlei Silva
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
Konstantin Donhauser, Javier Abad, Neha Hulkund et al.
Breaking through the learning plateaus of in-context learning in Transformer
Jingwen Fu, Tao Yang, Yuwang Wang et al.
Differentially Private Federated $k$-Means Clustering with Server-Side Data
Jonathan Scott, Christoph Lampert, David Saulpic
Off-policy Evaluation Beyond Overlap: Sharp Partial Identification Under Smoothness
Samir Khan, Martin Saveski, Johan Ugander
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
Seongsu Kim, Sungsoo Ahn
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning
Do-Yeon Kim, Dong-Jun Han, Jun Seo et al.
Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization
Nayeong Kim, Juwon Kang, Sungsoo Ahn et al.
Clustered Federated Learning via Gradient-based Partitioning
Heasung Kim, Hyeji Kim, Gustavo De Veciana
Demystifying SGD with Doubly Stochastic Gradients
Kyurae Kim, Joohwan Ko, Yian Ma et al.
Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient
Ju-Hyun Kim, Seungki Min
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.