Most Cited ICML "maximum-a-posteriori estimation" Papers
5,975 papers found • Page 26 of 30
Conference
Do Multiple Instance Learning Models Transfer?
Daniel Shao, Richard Chen, Andrew Song et al.
Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
Aaron Havens, Benjamin Kurt Miller, Bing Yan et al.
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition
Zheyang Xiong, Jack Cai, John Cooper et al.
Online Pre-Training for Offline-to-Online Reinforcement Learning
Yongjae Shin, Jeonghye Kim, Whiyoung Jung et al.
Learning Optimal Multimodal Information Bottleneck Representations
Qilong Wu, Yiyang Shao, Jun Wang et al.
UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction
Perampalli Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin et al.
Learning to Stop: Deep Learning for Mean Field Optimal Stopping
Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere
Interpreting CLIP with Hierarchical Sparse Autoencoders
Vladimir Zaigrajew, Hubert Baniecki, Przemysław Biecek
Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
YUTONG WU, Jie Zhang, Yiming Li et al.
Logarithmic Regret for Online KL-Regularized Reinforcement Learning
Heyang Zhao, Chenlu Ye, Wei Xiong et al.
MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving
Ruida Wang, Rui Pan, Yuxin Li et al.
Human Body Restoration with One-Step Diffusion Model and A New Benchmark
Jue Gong, Jingkai Wang, Zheng Chen et al.
Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs
Sagnik Mukherjee, Abhinav Chinta, Takyoung Kim et al.
ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
Utkarsh Saxena, Sayeh Sharify, Kaushik Roy et al.
A Trichotomy for List Transductive Online Learning
Steve Hanneke, Amirreza Shaeiri
Statistical Collusion by Collectives on Learning Platforms
Etienne Gauthier, Francis Bach, Michael Jordan
Origin Identification for Text-Guided Image-to-Image Diffusion Models
Wenhao Wang, Yifan Sun, Zongxin Yang et al.
Softmax is not Enough (for Sharp Size Generalisation)
Petar Veličković, Christos Perivolaropoulos, Federico Barbero et al.
Rejecting Hallucinated State Targets during Planning
Mingde Zhao, Tristan Sylvain, Romain Laroche et al.
Learning without Isolation: Pathway Protection for Continual Learning
Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui et al.
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao et al.
Normalizing Flows are Capable Generative Models
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran et al.
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska et al.
Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut et al.
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi et al.
TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference
Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera et al.
Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas
Shiqi Chen, Tongyao Zhu, Ruochen Zhou et al.
Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis et al.
Actor-Critics Can Achieve Optimal Sample Efficiency
Kevin Tan, Wei Fan, Yuting Wei
Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
Siqi Guo, Ilgee Hong, Vicente Balmaseda et al.
Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen
How Compositional Generalization and Creativity Improve as Diffusion Models are Trained
Alessandro Favero, Antonio Sclocchi, Francesco Cagnetta et al.
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
Jungtaek Kim
CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models
Lanyun Zhu, Deyi Ji, Tianrun Chen et al.
Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning
Eric Wang, Zhichao Chen, Haotian Wang et al.
Conditioning Diffusions Using Malliavin Calculus
Jakiw Pidstrigach, Elizabeth Baker, Carles Domingo i Enrich et al.
Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments
Baohong Li, Yingrong Wang, Anpeng Wu et al.
Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection
Peipeng Yu, Jianwei Fei, Hui Gao et al.
FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields
Gwanhyeong Koo, Sunjae Yoon, Younghwan Lee et al.
Uncertainty Quantification for LLM-Based Survey Simulations
Chengpiao Huang, Yuhang Wu, Kaizheng Wang
MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
Yuang Zhang, Jiaxi Gu, Li-Wen Wang et al.
MindAligner: Explicit Brain Functional Alignment for Cross-Subject Visual Decoding from Limited fMRI Data
Yuqin Dai, Zhouheng Yao, Chunfeng Song et al.
On Measuring Long-Range Interactions in Graph Neural Networks
Jacob Bamberger, Benjamin Gutteridge, Scott le Roux et al.
DyCodeEval: Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
Simin Chen, Pranav Pusarla, Baishakhi Ray
A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
Zhengzheng Lou, Hang Xue, Chaoyang Zhang et al.
Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
Xu Wang, Yan Hu, Wenyu Du et al.
Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
Ce Zhang, Yixin Han, Yafei Wang et al.
Average Sensitivity of Hierarchical $k$-Median Clustering
Shijie Li, Weiqiang He, Ruobing Bai et al.
Tool Unlearning for Tool-Augmented LLMs
Jiali Cheng, Hadi Amiri
Extreme Value Policy Optimization for Safe Reinforcement Learning
Shiqing Gao, Yihang Zhou, Shuai Shao et al.
One Arrow, Two Hawks: Sharpness-aware Minimization for Federated Learning via Global Model Trajectory
Yuhang Li, Tong Liu, Yangguang Cui et al.
Heavy-Tailed Linear Bandits: Huber Regression with One-Pass Update
Jing Wang, Yu-Jie Zhang, Peng Zhao et al.
Learning Imbalanced Data with Beneficial Label Noise
Guangzheng Hu, Feng Liu, Mingming Gong et al.
Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems
Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz et al.
Robust ML Auditing using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas et al.
Exogenous Isomorphism for Counterfactual Identifiability
Yikang Chen, Dehui du
CoSER: Coordinating LLM-Based Persona Simulation of Established Roles
Xintao Wang, Heng Wang, Yifei Zhang et al.
Wait-Less Offline Tuning and Re-solving for Online Decision Making
Jingruo Sun, Wenzhi Gao, Ellen Vitercik et al.
DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton et al.
LapSum - One Method to Differentiate Them All: Ranking, Sorting and Top-k Selection
Łukasz Struski, Michal Bednarczyk, Igor Podolak et al.
A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
Ruinan Jin, Xiao Li, Yaoliang Yu et al.
Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
David Vigouroux, Joseba Dalmau, Louis Béthune et al.
DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning
Gaoyue Zhou, Hengkai Pan, Yann LeCun et al.
Measuring Diversity in Synthetic Datasets
Yuchang Zhu, Huizhe Zhang, Bingzhe Wu et al.
Diffusion Instruction Tuning
Chen Jin, Ryutaro Tanno, Amrutha Saseendran et al.
Agent-as-a-Judge: Evaluate Agents with Agents
Mingchen Zhuge, Changsheng Zhao, Dylan Ashley et al.
RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
Yushuai Li, Hengyu Liu, Torben Pedersen et al.
Metadata Conditioning Accelerates Language Model Pre-training
Tianyu Gao, Alexander Wettig, Luxi He et al.
Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
Bingshan Hu, Zhiming Huang, Tianyue Zhang et al.
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
Lakshmi Nair, Ian Trase, J. Kim
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng, Wen Li, Zhaoqiang Liu
Energy-Based Preference Model Offers Better Offline Alignment than the Bradley-Terry Preference Model
Yuzhong Hong, Hanshan Zhang, Junwei Bao et al.
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer et al.
CombiMOTS: Combinatorial Multi-Objective Tree Search for Dual-Target Molecule Generation
Thibaud Southiratn, Bonil Koo, Yijingxiu Lu et al.
Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing
Kento Nishi, Rahul Ramesh, Maya Okawa et al.
Occult: Optimizing Collaborative Communications across Experts for Accelerated Parallel MoE Training and Inference
Shuqing Luo, Pingzhi Li, Jie Peng et al.
Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback
Tal Lancewicki, Yishay Mansour
Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences
Yunhong Lu, Qichao Wang, Hengyuan Cao et al.
Adversaries Can Misuse Combinations of Safe Models
Erik Jones, Anca Dragan, Jacob Steinhardt
Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
Kulin Shah, Alkis Kalavasis, Adam Klivans et al.
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu et al.
Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
Yunyi Shen, Hao Sun, Jean-Francois Ton
TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
Qihe Huang, Zhengyang Zhou, Kuo Yang et al.
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell et al.
A Variational Framework for Improving Naturalness in Generative Spoken Language Models
Li-Wei Chen, Takuya Higuchi, Zakaria Aldeneh et al.
Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
Huafeng Liu, Yiran Fu, Liping Jing et al.
LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models
Fanfei Li, Thomas Klein, Wieland Brendel et al.
Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence
Joseph Paillard, Angel REYERO LOBO, Vitaliy Kolodyazhniy et al.
LEAPS: A discrete neural sampler via locally equivariant networks
Peter Holderrieth, Michael Albergo, Tommi Jaakkola
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu et al.
FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Gabriel Müller et al.
AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao et al.
Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis et al.
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
Yassine Abbahaddou, Fragkiskos Malliaros, Johannes Lutzeyer et al.
Test-Time Canonicalization by Foundation Models for Robust Perception
Utkarsh Singhal, Ryan Feng, Stella Yu et al.
Trustworthy Machine Learning through Data-Specific Indistinguishability
Hanshen Xiao, Zhen Yang, Edward Suh
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach
Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar et al.
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
Preference Optimization for Combinatorial Optimization Problems
Mingjun Pan, Guanquan Lin, You-Wei Luo et al.
Improving Model Alignment Through Collective Intelligence of Open-Source Models
Junlin Wang, Roy Xie, Shang Zhu et al.
GradPS: Resolving Futile Neurons in Parameter Sharing Network for Multi-Agent Reinforcement Learning
Haoyuan Qin, Zhengzhu Liu, Chenxing Lin et al.
Do We Really Need Message Passing in Brain Network Modeling?
Liang Yang, Yuwei Liu, Jiaming Zhuo et al.
How Far Is Video Generation from World Model: A Physical Law Perspective
Bingyi Kang, Yang Yue, Rui Lu et al.
SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution
Wenwen He, Wenke Huang, Bin Yang et al.
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
On the Power of Context-Enhanced Learning in LLMs
Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.
Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
Tom Jacobs, Chao Zhou, Rebekka Burkholz
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, jiangtao wen, Yuxing Han
Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang et al.
DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models
Changyi He, Yifu Ding, Jinyang Guo et al.
Online Laplacian-Based Representation Learning in Reinforcement Learning
Maheed Ahmed, Jayanth Bhargav, Mahsa Ghasemi
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh
Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds
Emanuele Troiani, Hugo Cui, Yatin Dandi et al.
One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework
Feiran Li, Qianqian Xu, Shilong Bao et al.
Algorithms with Calibrated Machine Learning Predictions
Judy Hanwen Shen, Ellen Vitercik, Anders Wikum
Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
Tomer Meir, Uri Shalit, Malka Gorfine
Staged and Physics-Grounded Learning Framework with Hyperintensity Prior for Pre-Contrast MRI Synthesis
Dayang Wang, Srivathsa Pasumarthi Venkata, Ajit Shankaranarayanan et al.
SSHR: More Secure Generative Steganography with High-Quality Revealed Secret Images
Jiannian Wang, Yao Lu, Guangming Lu
FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation
Zheng Fang, Lichuan Xiang, Xu Cai et al.
Revisiting the Predictability of Performative, Social Events
Juan Perdomo
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan et al.
Nonconvex Theory of $M$-estimators with Decomposable Regularizers
Weiwei Liu
GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration
Yuhang Li, Ruokai Yin, Donghyun Lee et al.
PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
Chenyu Li, Oscar Michel, Xichen Pan et al.
From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium
Yi Xie, Zhanke Zhou, Chentao Cao et al.
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs
Akhiad Bercovich, Tomer Ronen, Talor Abramovich et al.
Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems
Shaokun Zhang, Ming Yin, Jieyu Zhang et al.
Customizing the Inductive Biases of Softmax Attention using Structured Matrices
Yilun Kuang, Noah Amsel, Sanae Lotfi et al.
RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
Payman Behnam, Yaosheng Fu, Ritchie Zhao et al.
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai, Pin-Han Huang, Bo-Han Kung et al.
DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning
Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.
Synthesizing Images on Perceptual Boundaries of ANNs for Uncovering and Manipulating Human Perceptual Variability
Chen Wei, Chi Zhang, Jiachen Zou et al.
The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret
Lukas Fluri, Leon Lang, Alessandro Abate et al.
Regret-Free Reinforcement Learning for Temporal Logic Specifications
R Majumdar, Mahmoud Salamati, Sadegh Soudjani
Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation
Chang Liu, Yixin Wang, Moontae Lee
Locality Preserving Markovian Transition for Instance Retrieval
Jifei Luo, Wenzheng Wu, Hantao Yao et al.
Fast Video Generation with Sliding Tile Attention
Peiyuan Zhang, Yongqi Chen, Runlong Su et al.
Natural Perturbations for Black-box Training of Neural Networks by Zeroth-Order Optimization
Hiroshi Sawada, Kazuo Aoyama, Yuya Hikima
ConText: Driving In-context Learning for Text Removal and Segmentation
Fei Zhang, Pei Zhang, Baosong Yang et al.
Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures
Yingzhao Jian, Yue Zhang, Ying Wei et al.
Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge
Hanglei Hu, Yingying Guo, Zhikang Chen et al.
Learning the Electronic Hamiltonian of Large Atomic Structures
Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas et al.
Diffusion Counterfactual Generation with Semantic Abduction
Rajat Rasal, Avinash Kori, Fabio De Sousa Ribeiro et al.
When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration
Suorong Yang, Peng Ye, Furao Shen et al.
Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics
Hongbin Pei, Jingxin Hai, Yu Li et al.
Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence
Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi et al.
Weakly-Supervised Contrastive Learning for Imprecise Class Labels
Zi-Hao Zhou, Jun-Jie Wang, Tong Wei et al.
Maintaining Proportional Committees with Dynamic Candidate Sets
Chris Dong, Jannik Peters
Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits
Jinzhao Li, Nan Jiang, Yexiang Xue
Exact Upper and Lower Bounds for the Output Distribution of Neural Networks with Random Inputs
Andrey Kofnov, Daniel Kapla, Ezio Bartocci et al.
Reward Translation via Reward Machine in Semi-Alignable MDPs
Yun Hua, Haosheng Chen, Wenhao Li et al.
TUMTraf VideoQA: Dataset and Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes
Xingcheng Zhou, Konstantinos Larintzakis, Hao Guo et al.
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries
Junhyuck Kim, Jongho Park, Jaewoong Cho et al.
Catching Two Birds with One Stone: Reward Shaping with Dual Random Networks for Balancing Exploration and Exploitation
Haozhe Ma, Fangling Li, Jing Lim et al.
Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
Xianliang Xu, Ye Li, Zhongyi Huang
On the Out-of-Distribution Generalization of Self-Supervised Learning
Wenwen Qiang, Jingyao Wang, Zeen Song et al.
Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection
Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
Diyuan Wu, Marco Mondelli
Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
Brett Barkley, David Fridovich-Keil
AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang et al.
Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
Fan Zhou, Zengzhi Wang, Qian Liu et al.
The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models
Zichao Li, Xueru Wen, Jie Lou et al.
Automated Red Teaming with GOAT: the Generative Offensive Agent Tester
Maya Pavlova, Erik Brinkman, Krithika Iyer et al.
Language Models May Verbatim Complete Text They Were Not Explicitly Trained On
Ken Ziyu Liu, Christopher A. Choquette Choo, Matthew Jagielski et al.
InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
Tianyu Cui, Song-Jun Xu, Artem Moskalev et al.
Polynomial-Time Approximability of Constrained Reinforcement Learning
Jeremy McMahan
Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
Qingchuan Ma, Yuhang Wu, Xiawu Zheng et al.
No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
Attila Szász, Balázs Bánhelyi, Mark Jelasity
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim et al.
Large Language Models are Demonstration Pre-Selectors for Themselves
Jiarui Jin, Yuwei Wu, Haoxuan Li et al.
WAVE: Weighted Autoregressive Varying Gate for Time Series Forecasting
Jiecheng Lu, Xu Han, Yan Sun et al.
Large Language-Geometry Model: When LLM meets Equivariance
Zongzhao Li, Jiacheng Cen, Bing Su et al.
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
Jinghan Li, Zhicheng Sun, Yadong Mu
Open Materials Generation with Stochastic Interpolants
Philipp Höllmer, Thomas Egg, Maya Martirossyan et al.
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao et al.
GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
Jinuk Kim, Marwa El Halabi, Wonpyo Park et al.
Attributes Shape the Embedding Space of Face Recognition Models
Pierrick Leroy, Antonio Mastropietro, Marco Nurisso et al.
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
Joshua Kazdan, Rylan Schaeffer, Apratim Dey et al.
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting
Jiecheng Lu, Shihao Yang
One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs
Yinghui Li, Jiayi Kuang, Haojing Huang et al.
Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee et al.
Control and Realism: Best of Both Worlds in Layout-to-Image without Training
Bonan Li, Yinhan Hu, Songhua Liu et al.
Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation
Tianyi Zhang, Junda Su, Aditya Desai et al.
Tracking Most Significant Shifts in Infinite-Armed Bandits
Joe Suk, Jung-hun Kim
When to Forget? Complexity Trade-offs in Machine Unlearning
Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia et al.
Direct Density Ratio Optimization: A Statistically Consistent Approach to Aligning Large Language Models
Rei Higuchi, Taiji Suzuki
M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation
Tao Zhang, Zhenhai Liu, Feipeng Qi et al.
Spherical Rotation Dimension Reduction with Geometric Loss Functions
Hengrui Luo, Jeremy E. Purvis, Didong Li
Improving the Scaling Laws of Synthetic Data with Deliberate Practice
Reyhane Askari Hemmat, Mohammad Pezeshki, Elvis Dohmatob et al.
Widening the Network Mitigates the Impact of Data Heterogeneity on FedAvg
Like Jian, Dong Liu
Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
Yihao Yang, Wenke Huang, Guancheng Wan et al.
Understanding High-Dimensional Bayesian Optimization
Leonard Papenmeier, Matthias Poloczek, Luigi Nardi
Learning Configurations for Data-Driven Multi-Objective Optimization
Zhiyang Chen, Hailong Yao, Xia Yin
End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao et al.
SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
Enze Xie, Junsong Chen, Yuyang Zhao et al.
Going Deeper into Locally Differentially Private Graph Neural Networks
Longzhu He, Chaozhuo Li, Peng Tang et al.
Federated Node-Level Clustering Network with Cross-Subgraph Link Mending
Jingxin Liu, Renda Han, Wenxuan Tu et al.