Most Cited ICML "supervised fine tuning" Papers

Statistical Test for Feature Selection Pipelines by Selective Inference

Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training

Chen Liu, Zhichao Huang, Mathieu Salzmann et al.

Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models

Shuoyuan Wang, Sharon Li, Hongxin Wei

Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization

Shira Vansover-Hager, Tomer Koren, Roi Livni

Hidden No More: Attacking and Defending Private Third-Party LLM Inference

Rahul Thomas, Louai Zahran, Erica Choi et al.

Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective

Daniel Franzen, Jan Disselhoff, David Hartmann

Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering

Zihan Song, Xin Wang, Zi Qian et al.

A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward

Zachary Roch, George Atia, Yue Wang

EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption

Leo de Castro, Daniel Escudero, Adya Agrawal et al.

How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical Perspective

Jing Qiao, Yu Liu, YUAN YUAN et al.

Provable Zero-Shot Generalization in Offline Reinforcement Learning

Zhiyong Wang, Chen Yang, John C. S. Lui et al.

Distillation Scaling Laws

Dan Busbridge, Amitis Shidani, Floris Weers et al.

FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain

Rohan Deb, Kiran Thekumparampil, Kousha Kalantari et al.

Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints

Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.

Neural Solver Selection for Combinatorial Optimization

Chengrui Gao, Haopu Shang, Ke Xue et al.

David and Goliath: Small One-step Model Beats Large Diffusion with Score Post-training

Weijian Luo, colin zhang, Debing Zhang et al.

KinDEL: DNA-Encoded Library Dataset for Kinase Inhibitors

Benson Chen, Tomasz Danel, Gabriel Dreiman et al.

System-Aware Unlearning Algorithms: Use Lesser, Forget Faster

Linda Lu, Ayush Sekhari, Karthik Sridharan

Channel Normalization for Time Series Channel Identification

Seunghan Lee, Taeyoung Park, Kibok Lee

Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization

Kyurae Kim, Zuheng Xu, Jacob Gardner et al.

Closed-form Solutions: A New Perspective on Solving Differential Equations

Shu Wei, Yanjie Li, Lina Yu et al.

SSHR: More Secure Generative Steganography with High-Quality Revealed Secret Images

Jiannian Wang, Yao Lu, Guangming Lu

Synthesizing Software Engineering Data in a Test-Driven Manner

Lei Zhang, Jiaxi Yang, Min Yang et al.

FedClean: A General Robust Label Noise Correction for Federated Learning

Xiaoqian Jiang, Jing Zhang

Adaptive Sensitivity Analysis for Robust Augmentation against Natural Corruptions in Image Segmentation

Laura Zheng, Wenjie Wei, Tony Wu et al.

Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach

Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.

Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees

Tomer Meir, Uri Shalit, Malka Gorfine

Learning with Exact Invariances in Polynomial Time

Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka et al.

Banyan: Improved Representation Learning with Explicit Structure

Mattia Opper, Siddharth N

Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements

Manwen Liao, Yan Zhu, Weitian Zhang et al.

Understanding the Logic of Direct Preference Alignment through Logic

Kyle Richardson, Vivek Srikumar, Ashish Sabharwal

Diffusion Adversarial Post-Training for One-Step Video Generation

Shanchuan Lin, Xin Xia, Yuxi Ren et al.

Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations

Jason Qin, Hans-Hermann Wessels, Carlos Fernandez-Granda et al.

The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability

Jiachen Hu, Rui Ai, Han Zhong et al.

NestQuant: nested lattice quantization for matrix products and LLMs

Semyon Savkin, Eitan Porat, Or Ordentlich et al.

Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry

Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.

Differentially Private Space-Efficient Algorithms for Counting Distinct Elements in the Turnstile Model

Rachel Cummings, Alessandro Epasto, Jieming Mao et al.

An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks

Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh

Cross-City Latent Space Alignment for Consistency Region Embedding

Meng Chen, Hongwei Jia, Zechen Li et al.

DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing

Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou

Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent

Ya-Chi Chu, Wenzhi Gao, Yinyu Ye et al.

Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints

Hengquan Guo, Lingkai Zu, Xin Liu

RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior

Ching-Hua Lee, Chouchang Yang, Jaejin Cho et al.

Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions

Yik Siu Chan, Narutatsu Ri, Yuxin Xiao et al.

Steering Protein Language Models

Long-Kai Huang, Rongyi Zhu, Bing He et al.

Online Laplacian-Based Representation Learning in Reinforcement Learning

Maheed Ahmed, Jayanth Bhargav, Mahsa Ghasemi

MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training

Yang Luo, Zangwei Zheng, Ziheng Qin et al.

COMRECGC: Global Graph Counterfactual Explainer through Common Recourse

Gregoire Fournier, Sourav Medya

MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models

Jeffrey A. Chan-Santiago, praveen tirupattur, Gaurav Kumar Nayak et al.

Deep Neural Cellular Potts Models

Koen Minartz, Tim d'Hondt, Leon Hillmann et al.

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.

High-Dimensional Prediction for Sequential Decision Making

Georgy Noarov, Ramya Ramalingam, Aaron Roth 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

Whitened CLIP as a Likelihood Surrogate of Images and Captions

Roy Betser, Meir Yossef Levi, Guy Gilboa

Hypothesis Testing for Generalized Thurstone Models

Anuran Makur, Japneet Singh

Multi-Objective Causal Bayesian Optimization

Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.

An Efficient Private GPT Never Autoregressively Decodes

Zhengyi Li, Yue Guan, Kang Yang et al.

An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints

Jiahui Zhu, Kihyun Yu, Dabeen Lee et al.

FEAT-KD: Learning Concise Representations for Single and Multi-Target Regression via TabNet Knowledge Distillation

Kei Sen Fong, Mehul Motani

Staged and Physics-Grounded Learning Framework with Hyperintensity Prior for Pre-Contrast MRI Synthesis

Dayang Wang, Srivathsa Pasumarthi Venkata, Ajit Shankaranarayanan et al.

MissScore: High-Order Score Estimation in the Presence of Missing Data

Wenqin Liu, Haoze Hou, Erdun Gao et al.

ADDQ: Adaptive distributional double Q-learning

Leif Döring, Benedikt Wille, Maximilian Birr et al.

From Complex to Atomic: Enhancing Augmented Generation via Knowledge-Aware Dual Rewriting and Reasoning

Jinyu Wang, Jingjing Fu, Rui Wang et al.

ExpProof : Operationalizing Explanations for Confidential Models with ZKPs

Chhavi Yadav, Evan Laufer, Dan Boneh et al.

FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation

Zheng Fang, Lichuan Xiang, Xu Cai et al.

DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models

Changyi He, Yifu Ding, Jinyang Guo et al.

QMamba: On First Exploration of Vision Mamba for Image Quality Assessment

Fengbin Guan, Xin Li, Zihao Yu et al.

ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning

Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.

Conformity Score Averaging for Classification

Rui Luo, Zhixin Zhou

Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization

Zelai Xu, Wanjun Gu, Chao Yu et al.

GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation

Mengzhu Wang, houcheng su, Jiao Li 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.

Learnings from Scaling Visual Tokenizers for Reconstruction and Generation

Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang et al.

An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective

Xinyue Chen, Jinfeng Peng, Yuhao Li et al.

Nonconvex Theory of $M$-estimators with Decomposable Regularizers

Weiwei Liu

RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation

Xinnuo Xu, Rachel Lawrence, Kshitij Dubey et al.

Evolving Minds: Logic-Informed Inference from Temporal Action Patterns

Chao Yang, Shuting Cui, Yang Yang et al.

Certified Unlearning for Neural Networks

Anastasiia Koloskova, Youssef Allouah, Animesh Jha et al.

Star Attention: Efficient LLM Inference over Long Sequences

Shantanu Acharya, Fei Jia, Boris Ginsburg

GPTAQ: Efficient Finetuning-Free Quantization for Asymmetric Calibration

Yuhang Li, Ruokai Yin, Donghyun Lee et al.

Scaling Sparse Feature Circuits For Studying In-Context Learning

Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.

Towards Better-than-2 Approximation for Constrained Correlation Clustering

Andreas Kalavas, Evangelos Kipouridis, Nithin Varma

Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models

Xingyu Chen, Jiahao Xu, Tian Liang et al.

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees

Haonan Yuan, Qingyun Sun, Junhua Shi et al.

KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search

Haoran Luo, Haihong E, Yikai Guo et al.

FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning

Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.

Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View Learning

Xue Zhao, Qinying Gu, Xinbing Wang et al.

Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Haoqi Wu, Wei Dai, Wang Li et al.

Zero-Shot Generalization of GNNs over Distinct Attribute Domains

Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua et al.

PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop

Chenyu Li, Oscar Michel, Xichen Pan et al.

AAAR-1.0: Assessing AI’s Potential to Assist Research

Renze Lou, Hanzi Xu, Sijia Wang et al.

Equivariant Polynomial Functional Networks

Thieu Vo, Viet Hoang Tran, Tho Tran Huu et al.

From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium

Yi Xie, Zhanke Zhou, Chentao Cao et al.

Residual Matrix Transformers: Scaling the Size of the Residual Stream

Brian Mak, Jeffrey Flanigan

Latent Mamba Operator for Partial Differential Equations

Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.

Puzzle: Distillation-Based NAS for Inference-Optimized LLMs

Akhiad Bercovich, Tomer Ronen, Talor Abramovich et al.

BackSlash: Rate Constrained Optimized Training of Large Language Models

Jun Wu, jiangtao wen, Yuxing Han

ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features

Alec Helbling, Tuna Han Salih Meral, Benjamin Hoover et al.

Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks

Rui Xue, Tong Zhao, Neil Shah et al.

An Efficient Search-and-Score Algorithm for Ancestral Graphs using Multivariate Information Scores for Complex Non-linear and Categorical Data

Nikita Lagrange, Herve Isambert

MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning

Zihan Chen, Song Wang, Zhen Tan et al.

Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment

Xingyu Zhou, Yulian Wu, Wenqian Weng et al.

Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?

Tom Jacobs, Chao Zhou, Rebekka Burkholz

Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss

Bo-Han Lai, Pin-Han Huang, Bo-Han Kung et al.

Gridded Transformer Neural Processes for Spatio-Temporal Data

Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.

Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective

Yunzhen Yao, Lie He, Michael Gastpar

Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks

Yixin Cheng, Hongcheng Guo, Yangming Li et al.

DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning

Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.

IT$^3$: Idempotent Test-Time Training

Nikita Durasov, Assaf Shocher, Doruk Oner 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.

When and How Does CLIP Enable Domain and Compositional Generalization?

Elias Kempf, Simon Schrodi, Max Argus et al.

Counterfactual Voting Adjustment for Quality Assessment and Fairer Voting in Online Platforms with Helpfulness Evaluation

Chang Liu, Yixin Wang, Moontae Lee

Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework

Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

Parshin Shojaee, Ngoc Hieu Nguyen, Kazem Meidani et al.

Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton

Chengmei Niu, Zhenyu Liao, Zenan Ling et al.

Retrieval-Augmented Language Model for Knowledge-aware Protein Encoding

Zhang Jiasheng, Delvin Zhang, Shuang Liang et al.

Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits

Su Jia, Peter Frazier, Nathan Kallus

Locality Preserving Markovian Transition for Instance Retrieval

Jifei Luo, Wenzheng Wu, Hantao Yao et al.

Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$ Parametrization

Zixiang Chen, Greg Yang, Qingyue Zhao et al.

Adapting Precomputed Features for Efficient Graph Condensation

Yuan Li, Jun Hu, Zemin Liu et al.

TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization

Songtao Lu

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger

Qi Yang, Chenghao Zhang, Lubin Fan et al.

One-Step Generalization Ratio Guided Optimization for Domain Generalization

Sumin Cho, Dongwon Kim, Kwangsu Kim

Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape

Tao Li, Zhengbao He, Yujun Li et al.

Trusted Multi-View Classification with Expert Knowledge Constraints

Xinyan Liang, Shijie Wang, Yuhua Qian et al.

Fast Video Generation with Sliding Tile Attention

Peiyuan Zhang, Yongqi Chen, Runlong Su et al.

Sleeping Reinforcement Learning

Simone Drago, Marco Mussi, Alberto Maria Metelli

UnHiPPO: Uncertainty-aware Initialization for State Space Models

Marten Lienen, Abdullah Saydemir, Stephan Günnemann

Preference learning made easy: Everything should be understood through win rate

Lily Zhang, Rajesh Ranganath

Super Deep Contrastive Information Bottleneck for Multi-modal Clustering

Zhengzheng Lou, Ke Zhang, Yucong Wu et al.

Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks

Liyuan Liang, Xinyi Chen, Gan Luo et al.

Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds

Aya Kayal, Sattar Vakili, Laura Toni et al.

A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization

Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.

LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification

Hang Gao, Huang Wenxuan, Fengge Wu et al.

Self-Consuming Generative Models with Adversarially Curated Data

Xiukun Wei, Xueru Zhang

Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold

Yilong Song, Peijin Li, Bin Gao et al.

Improving Out-of-Distribution Detection via Dynamic Covariance Calibration

Kaiyu Guo, Zijian Wang, Tan Pan et al.

OmniArch: Building Foundation Model for Scientific Computing

Tianyu Chen, Haoyi Zhou, Ying Li 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.

Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective

Hechuan Wen, Tong Chen, Mingming Gong et al.

Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms

Sho Takemori, Yuhei Umeda, Aditya Gopalan

Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem

In Huh, Changwook Jeong, Muhammad Alam

On the Power of Context-Enhanced Learning in LLMs

Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora

FG-CLIP: Fine-Grained Visual and Textual Alignment

Chunyu Xie, Bin Wang, Fanjing Kong et al.

Online Linear Classification with Massart Noise

Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos et al.

Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement

Yuheng Jing, Kai Li, Bingyun Liu et al.

Stay-Positive: A Case for Ignoring Real Image Features in Fake Image Detection

Anirudh Sundara Rajan, Yong Jae Lee

HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training

Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.

Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization

Ziyu Gong, Jim Lim, David I. Inouye

PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis

Sunghwan Hong, Jaewoo Jung, Heeseong Shin et al.

AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism

Zhepei Wei, Wei-Lin Chen, Xinyu Zhu et al.

InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective

Yuanhong Zhang, Muyao Yuan, Weizhan Zhang et al.

Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge

Hanglei Hu, Yingying Guo, Zhikang Chen et al.

On the Statistical Mechanisms of Distributional Compositional Generalization

Jingwen Fu, Nanning Zheng

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning

Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows

Gabriele Visentin, Patrick Cheridito

Interpreting the Repeated Token Phenomenon in Large Language Models

Itay Yona, Ilia Shumailov, Jamie Hayes et al.

Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series

Zachary Brown, David Carlson

Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling

Shuqi Lu, Xiaohong Ji, Bohang Zhang et al.

TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks

Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro et al.

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks

Jeongmo Kim, Yisak Park, Minung Kim et al.

Diffusion Counterfactual Generation with Semantic Abduction

Rajat Rasal, Avinash Kori, Fabio De Sousa Ribeiro et al.

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data

Corinna Cortes, Anqi Mao, Mehryar Mohri et al.

InfAlign: Inference-aware language model alignment

Ananth Balashankar, Ziteng Sun, Jonathan Berant et al.

Learning Safe Control via On-the-Fly Bandit Exploration

Alexandre Capone, Ryan Cosner, Aaron Ames et al.

Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG

Wenbin Wang, Yongcheng Jing, Liang Ding et al.

Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster

Sharan Vaswani, Reza Babanezhad

LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning

Zihang Liu, Tianyu Pang, Oleg Balabanov et al.

K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes

Hideaki Kim, Tomoharu Iwata, Akinori Fujino

Large Continual Instruction Assistant

Jingyang Qiao, zhizhong zhang, Xin Tan et al.

Offline Model-based Optimization for Real-World Molecular Discovery

Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.

Expected Variational Inequalities

Brian Zhang, Ioannis Anagnostides, Emanuel Tewolde 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.

Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling

Xinxing Shi, Xiaoyu Jiang, Mauricio Álvarez

Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra

Raphael Meyer, William Swartworth, David Woodruff

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks

Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.

Beyond Induction Heads: In-Context Meta Learning Induces Multi-Phase Circuit Emergence

Gouki Minegishi, Hiroki Furuta, Shohei Taniguchi et al.

LETS Forecast: Learning Embedology for Time Series Forecasting

Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.

FreeMesh: Boosting Mesh Generation with Coordinates Merging

Jian Liu, Haohan Weng, Biwen Lei et al.

Maintaining Proportional Committees with Dynamic Candidate Sets

Chris Dong, Jannik Peters

Optimal Transfer Learning for Missing Not-at-Random Matrix Completion

Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.

QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search

Zongyu Lin, Yao Tang, Xingcheng Yao et al.

The Jailbreak Tax: How Useful are Your Jailbreak Outputs?

Kristina Nikolić, Luze Sun, Jie Zhang et al.

One Wave To Explain Them All: A Unifying Perspective On Feature Attribution

Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.

SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution

Wenwen He, Wenke Huang, Bin Yang et al.

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning

Le-Trung Nguyen, Aël Quélennec, Van-Tam Nguyen et al.

How Far Is Video Generation from World Model: A Physical Law Perspective

Bingyi Kang, Yang Yue, Rui Lu et al.

Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts

Haoyang Li, Xin Wang, Xueling Zhu 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.

Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales

Ju-Seung Byun, Andrew Perrault

Towards Memorization Estimation: Fast, Formal and Free

Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.

Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning

Zhiyao Zhang, Myeung Suk Oh, Hairi et al.

PASS: Private Attributes Protection with Stochastic Data Substitution

Yizhuo Chen, Chun-Fu (Richard) Chen, Hsiang Hsu et al.

UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design

Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.

SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds

Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.