Most Cited ICML "augmentation invariance" Papers

CSG-ODE: ControlSynth Graph ODE For Modeling Complex Evolution of Dynamic Graphs

Zhiqiang Wang, Xiaoyi Wang, Jianqing Liang

SAFER: A Calibrated Risk-Aware Multimodal Recommendation Model for Dynamic Treatment Regimes

Yishan Shen, Yuyang Ye, Hui Xiong et al.

SafeArena: Evaluating the Safety of Autonomous Web Agents

Ada Tur, Nicholas Meade, Xing Han Lù et al.

Scaling Large Motion Models with Million-Level Human Motions

Ye Wang, Sipeng Zheng, Bin Cao et al.

Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?

Konrad Mundinger, Max Zimmer, Aldo Kiem et al.

QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache

Rishabh Tiwari, Haocheng Xi, Aditya Tomar et al.

Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data

Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar

GPEN: Global Position Encoding Network for Enhanced Subgraph Representation Learning

Nannan Wu, Yuming Huang, Yiming Zhao et al.

Kinetic Langevin Diffusion for Crystalline Materials Generation

François Cornet, Federico Bergamin, Arghya Bhowmik et al.

On Understanding Attention-Based In-Context Learning for Categorical Data

Aaron Wang, William Convertino, Xiang Cheng et al.

Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead

Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee

Weak-to-Strong Jailbreaking on Large Language Models

Xuandong Zhao, Xianjun Yang, Tianyu Pang et al.

A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability

Pouria Fatemi, Ehsan Sharifian, Mohammad Hossein Yassaee

A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

Zhiyang Wang, Juan Cervino, Alejandro Ribeiro

Geometric Representation Condition Improves Equivariant Molecule Generation

Zian Li, Cai Zhou, Xiyuan Wang et al.

SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference

Jintao Zhang, Chendong Xiang, Haofeng Huang et al.

Prediction-Powered Adaptive Shrinkage Estimation

Sida Li, Nikolaos Ignatiadis

Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms

Christian Komusiewicz, André Schidler, Frank Sommer et al.

ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation

Tianci Bu, Le Zhou, Wenchuan Yang et al.

Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning

Seungho Baek, Taegeon Park, Jongchan Park et al.

$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting

Xingjian Wu, Xiangfei Qiu, Hongfan Gao et al.

Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision

Anqi Lu, Junchi Yan

Unified Screening for Multiple Diseases

Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar et al.

Generalization and Robustness of the Tilted Empirical Risk

Gholamali Aminian, Amir R. Asadi, Tian Li et al.

TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation

Hyeongwon Jang, Changhun Kim, Eunho Yang

Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models

Xin Cheng, Jiabo Ye, Haiyang Xu et al.

Diving into Self-Evolving Training for Multimodal Reasoning

Wei Liu, Junlong Li, Xiwen Zhang et al.

Sample-specific Noise Injection for Diffusion-based Adversarial Purification

Yuhao Sun, Jiacheng Zhang, Zesheng Ye et al.

Segment Anyword: Mask Prompt Inversion for Open-Set Grounded Segmentation

Zhihua Liu, Amrutha Saseendran, Lei Tong et al.

Attention-Level Speculation

Jack Cai, Ammar Vora, Randolph Zhang et al.

GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity Extrapolation

Jiashu HE, Mingyu Ma, Jinxuan Fan et al.

An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks

Valentyn Boreiko, Alexander Panfilov, Václav Voráček et al.

Feature Shift Localization Network

Míriam Barrabés, Daniel Mas Montserrat, Kapal Dev et al.

Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models

Yinhong Liu, Zhijiang Guo, Tianya Liang et al.

Toward Data-centric Directed Graph Learning: An Entropy-driven Approach

Xunkai Li, Zhengyu Wu, Kaichi Yu et al.

Enhancing Foundation Models with Federated Domain Knowledge Infusion

Jiaqi Wang, Jingtao Li, Weiming Zhuang et al.

"Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift

Harvineet Singh, Fan Xia, Alexej Gossmann et al.

Great Models Think Alike and this Undermines AI Oversight

Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina et al.

Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts

Yike Yuan, Ziyu Wang, Zihao Huang et al.

Mixture of Experts Made Intrinsically Interpretable

Xingyi Yang, Constantin Venhoff, Ashkan Khakzar et al.

Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer

Yihang Wang, Yuying Qiu, Peng Chen et al.

When to retrain a machine learning model

Florence Regol, Leo Schwinn, Kyle Sprague et al.

Pareto-frontier Entropy Search with Variational Lower Bound Maximization

Masanori Ishikura, Masayuki Karasuyama

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching

Aaron Havens, Benjamin Kurt Miller, Bing Yan et al.

Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails

Jindong Tong, Hongcheng Liu, Johannes Royset

Learn Singularly Perturbed Solutions via Homotopy Dynamics

Chuqi CHEN, Yahong Yang, Yang Xiang et al.

BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training

Chenyi yang, Wenjie Nie, Yuxin Zhang et al.

Automated Benchmark Generation for Repository-Level Coding Tasks

Konstantinos Vergopoulos, Mark Müller, Martin Vechev

DeepLayout: Learning Neural Representations of Circuit Placement Layout

Yuxiang Zhao, zhuomin chai, Xun Jiang et al.

CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models

Sen Peng, Mingyue Wang, Jianfei He et al.

Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding

Ziyao Wang, Muneeza Azmat, Ang Li et al.

Reinforcement Learning for Quantum Control under Physical Constraints

Jan Ole Ernst, Aniket Chatterjee, Tim Franzmeyer et al.

Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks

Etienne Boursier, Nicolas Flammarion

Online Pre-Training for Offline-to-Online Reinforcement Learning

Yongjae Shin, Jeonghye Kim, Whiyoung Jung et al.

Compute or Load KV Cache? Why Not Both?

Shuowei Jin, Xueshen Liu, Qingzhao Zhang et al.

UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction

Perampalli Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin et al.

Online Differentially Private Conformal Prediction for Uncertainty Quantification

CAD-Editor: A Locate-then-Infill Framework with Automated Training Data Synthesis for Text-Based CAD Editing

Yu Yuan, Shizhao Sun, Qi Liu et al.

AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings

Yilin Ye, Junchao Huang, Xingchen ZENG et al.

TimeStacker: A Novel Framework with Multilevel Observation for Capturing Nonstationary Patterns in Time Series Forecasting

Qinglong Liu, Cong Xu, Wenhao Jiang et al.

Learning to Stop: Deep Learning for Mean Field Optimal Stopping

Lorenzo Magnino, Yuchen Zhu, Mathieu Lauriere

Prior Knowledge Guided Neural Architecture Generation

Jingrong Xie, Han Ji, Yanan Sun

Gradient Aligned Regression via Pairwise Losses

Dixian Zhu, Tianbao Yang, Livnat Jerby

AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration

Wenhao SUN, Rong-Cheng Tu, Jingyi Liao et al.

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.

Fine-Grained Captioning of Long Videos through Scene Graph Consolidation

Sanghyeok Chu, Seonguk Seo, Bohyung Han

Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization

Xinyu Luo, Cedar Site Bai, Bolian Li 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.

FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models

Xinting Liao, Weiming Liu, Jiaming Qian et al.

Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity

Alessandro Montenegro, Marco Mussi, Matteo Papini et al.

ADIOS: Antibody Development via Opponent Shaping

Sebastian Towers, Aleksandra Kalisz, Philippe Robert et al.

Probabilistic Factorial Experimental Design for Combinatorial Interventions

Divya Shyamal, Jiaqi Zhang, Caroline Uhler

WikiBigEdit: Understanding the Limits of Lifelong Knowledge Editing in LLMs

Lukas Thede, Karsten Roth, Matthias Bethge et al.

Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network

Jijia Liu, Feng Gao, Qingmin Liao et al.

Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs

Sagnik Mukherjee, Abhinav Chinta, Takyoung Kim et al.

Habitizing Diffusion Planning for Efficient and Effective Decision Making

Haofei Lu, Yifei Shen, Dongsheng Li 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

Random Registers for Cross-Domain Few-Shot Learning

Shuai Yi, Yixiong Zou, Yuhua Li et al.

The Missing Alignment Link of In-context Learning on Sequences

Harshvardhan Agarwal, Sunita Sarawagi

Fast Tensor Completion via Approximate Richardson Iteration

Mehrdad Ghadiri, Matthew Fahrbach, Yunbum Kook et al.

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.

A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Attention Networks

Biswadeep Chakraborty, Harshit Kumar, Saibal Mukhopadhyay

No Metric to Rule Them All: Toward Principled Evaluations of Graph-Learning Datasets

Corinna Coupette, Jeremy Wayland, Emily Simons et al.

Rejecting Hallucinated State Targets during Planning

Mingde Zhao, Tristan Sylvain, Romain Laroche et al.

Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation

Kosuke Nakanishi, Akihiro Kubo, Yuji Yasui et al.

A First-order Generative Bilevel Optimization Framework for Diffusion Models

Quan Xiao, Hui Yuan, A F M Saif et al.

Algorithm Development in Neural Networks: Insights from the Streaming Parity Task

Loek van Rossem, Andrew Saxe

Learning without Isolation: Pathway Protection for Continual Learning

Zhikang Chen, Abudukelimu Wuerkaixi, Sen Cui et al.

Improving LLM Video Understanding with 16 Frames Per Second

Yixuan Li, Changli Tang, Jimin Zhuang et al.

Optimal Survey Design for Private Mean Estimation

Yu-Wei Chen, Raghu Pasupathy, Jordan A Awan

MARS: Unleashing the Power of Variance Reduction for Training Large Models

Huizhuo Yuan, Yifeng Liu, Shuang Wu et al.

Learning Imperfect Information Extensive-form Games with Last-iterate Convergence under Bandit Feedback

Canzhe Zhao, Yutian Cheng, Jing Dong et al.

Constrained Pareto Set Identification with Bandit Feedback

Cyrille Kone, Emilie Kaufmann, Laura Richert

BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing

Dongliang Guo, Mengxuan Hu, Zihan Guan et al.

Emergence in non-neural models: grokking modular arithmetic via average gradient outer product

Neil Mallinar, Daniel Beaglehole, Libin Zhu et al.

Autoformulation of Mathematical Optimization Models Using LLMs

Nicolás Astorga, Tennison Liu, Yuanzhang Xiao et al.

Quadratic Upper Bound for Boosting Robustness

Euijin You, Hyang-Won Lee

Geometric Generative Modeling with Noise-Conditioned Graph Networks

Peter Pao-Huang, Mitchell Black, Xiaojie Qiu

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills

Aidan Curtis, Eric Li, Michael S Noseworthy et al.

Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach

Qian Peng, Yajie Bao, Haojie Ren et al.

Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions

Jiahua Rao, Dahao Xu, Wentao Wei et al.

Normalizing Flows are Capable Generative Models

Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran et al.

Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization

Cameron Jakub, Mihai Nica

Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery

Mateusz Olko, Mateusz Gajewski, Joanna Wojciechowska et al.

Latent Action Learning Requires Supervision in the Presence of Distractors

Alexander Nikulin, Ilya Zisman, Denis Tarasov et al.

Improving Out-of-Distribution Detection with Markov Logic Networks

Konstantin Kirchheim, Frank Ortmeier

KernelBench: Can LLMs Write Efficient GPU Kernels?

Anne Ouyang, Simon Guo, Simran Arora et al.

DIS-CO: Discovering Copyrighted Content in VLMs Training Data

André Duarte, Xuandong Zhao, Arlindo Oliveira 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.

TRUST-VLM: Thorough Red-Teaming for Uncovering Safety Threats in Vision-Language Models

Kangjie Chen, Muyang Li, Guanlin Li et al.

TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference

Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera et al.

Safe-EF: Error Feedback for Non-smooth Constrained Optimization

Rustem Islamov, Yarden As, Ilyas Fatkhullin

Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas

Shiqi Chen, Tongyao Zhu, Ruochen Zhou et al.

Understanding Synthetic Context Extension via Retrieval Heads

Xinyu Zhao, Fangcong Yin, Greg Durrett

Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation

Juno Kim, Denny Wu, Jason Lee et al.

Learning Mean Field Control on Sparse Graphs

Christian Fabian, Kai Cui, Heinz Koeppl

How Effective Can Dropout Be in Multiple Instance Learning ?

Wenhui Zhu, Peijie Qiu, Xiwen Chen et al.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving

Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.

BDC-CLIP: Brownian Distance Covariance for Adapting CLIP to Action Recognition

Fei Long, Xiaoou Li, jiaming Lv et al.

Provably Efficient Exploration in Inverse Constrained Reinforcement Learning

Bo Yue, Jian Li, Guiliang Liu

Improving Compositional Generation with Diffusion Models Using Lift Scores

Chenning Yu, Sicun Gao

Direct Motion Models for Assessing Generated Videos

Kelsey Allen, Carl Doersch, Guangyao Zhou et al.

Adaptive Flow Matching for Resolving Small-Scale Physics

Stathi Fotiadis, Noah Brenowitz, Tomas Geffner et al.

Generalized Random Forests Using Fixed-Point Trees

David Fleischer, David A Stephens, Archer Yang

DiLQR: Differentiable Iterative Linear Quadratic Regulator via Implicit Differentiation

Shuyuan Wang, Philip D. Loewen, Michael Forbes 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.

PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs

Jianqing Zhang, Yang Liu, Jie Fu et al.

CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition

Zebin Wang, Menghan Lin, Bolin Shen et al.

X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP

Hanxun Huang, Sarah Erfani, Yige Li et al.

EcoMapper: Generative Modeling for Climate-Aware Satellite Imagery

Muhammed Göktepe, Amir Hossein Shamseddin, Erencan Uysal et al.

Multivariate Conformal Selection

Tian Bai, Yue Zhao, Xiang Yu et al.

Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding

Mingyu Jin, Kai Mei, Wujiang Xu et al.

Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics

Aleksandr Gushchin, Khaled Abud, Georgii Bychkov et al.

How Compositional Generalization and Creativity Improve as Diffusion Models are Trained

Alessandro Favero, Antonio Sclocchi, Francesco Cagnetta et al.

A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models

Shivam Kumar, Yun Yang, Lizhen Lin

Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning

Cheol Kim, Jai Moondra, Shresth Verma et al.

LightGTS: A Lightweight General Time Series Forecasting Model

Yihang Wang, Yuying Qiu, Peng Chen et al.

Revisiting Differentially Private Algorithms for Decentralized Online Learning

Xiaoyu Wang, Wenhao Yang, Chang Yao et al.

NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations

Myunsoo Kim, Hayeong Lee, Seong-Woong Shim et al.

Federated Oriented Learning: A Practical One-Shot Personalized Federated Learning Framework

Guan Huang, Tao Shu

Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models

Siddarth Venkatraman, Mohsin Hasan, Minsu Kim et al.

Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning

Jungtaek Kim

sciLaMA: A Single-Cell Representation Learning Framework to Leverage Prior Knowledge from Large Language Models

Hongru Hu, Shuwen Zhang, Yongin Choi et al.

Linear convergence of Sinkhorn's algorithm for generalized static Schrödinger bridge

Rahul Choudhary, Hanbaek Lyu

Equivalence is All: A Unified View for Self-supervised Graph Learning

Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.

EPIC: Efficient Position-Independent Caching for Serving Large Language Models

JUNHAO HU, Wenrui Huang, Weidong Wang et al.

ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models

Xinpeng Dong, Min Zhang, Didi Zhu et al.

Improved Off-policy Reinforcement Learning in Biological Sequence Design

Hyeonah Kim, Minsu Kim, Taeyoung Yun et al.

Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization

Simone Bombari, Marco Mondelli

CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models

Lanyun Zhu, Deyi Ji, Tianrun Chen et al.

Understanding Nonlinear Implicit Bias via Region Counts in Input Space

Jingwei Li, Jing Xu, Zifan Wang et al.

SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations

Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth

Federated Learning for Feature Generalization with Convex Constraints

Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.

Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning

Eric Wang, Zhichao Chen, Haotian Wang et al.

From Theory to Practice: Rethinking Green and Martin Kernels for Unleashing Graph Transformers

Yoon Hyeok Lee, Jaemin Park, Taejin Paik et al.

Conditioning Diffusions Using Malliavin Calculus

Jakiw Pidstrigach, Elizabeth Baker, Carles Domingo i Enrich et al.

MindCustomer: Multi-Context Image Generation Blended with Brain Signal

Muzhou Yu, Shuyun Lin, Lei Ma et al.

Empirical Design in Reinforcement Learning

Andrew Patterson, Samuel F Neumann, Martha White et al.

Compressed and distributed least-squares regression: convergence rates with applications to federated learning

Constantin Philippenko, Aymeric Dieuleveut

Spatial Reasoning with Denoising Models

Christopher Wewer, Bartlomiej Pogodzinski, Bernt Schiele et al.

ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization

Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson et al.

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

Xu Liu, Juncheng Liu, Gerald Woo et al.

Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments

Baohong Li, Yingrong Wang, Anpeng Wu et al.

Position: Stop treating `AGI' as the north-star goal of AI research

Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li et al.

COSDA: Counterfactual-based Susceptibility Risk Framework for Open-Set Domain Adaptation

Wenxu Wang, Rui Zhou, Jing Wang et al.

MARGE: Improving Math Reasoning with Guided Exploration

Jingyue Gao, Runji Lin, Keming Lu et al.

Physics Aware Neural Networks for Unsupervised Binding Energy Prediction

Ke Liu, Hao Chen, Chunhua Shen

Partially Observable Reinforcement Learning with Memory Traces

Onno Eberhard, Michael Muehlebach, Claire Vernade

Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection

Peipeng Yu, Jianwei Fei, Hui Gao et al.

How Do Large Language Monkeys Get Their Power (Laws)?

Rylan Schaeffer, Joshua Kazdan, John Hughes et al.

The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning

Dulhan Jayalath, Gilad Landau, Brendan Shillingford et al.

FlowDrag: 3D-aware Drag-based Image Editing with Mesh-guided Deformation Vector Flow Fields

Gwanhyeong Koo, Sunjae Yoon, Younghwan Lee et al.

Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters

Sijia Zhang, Shuli Zeng, Shaoang Li et al.

Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)

Kevin Wei, Patricia Paskov, Sunishchal Dev et al.

Modified K-means Algorithm with Local Optimality Guarantees

Mingyi Li, Michael R. Metel, Akiko Takeda

Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer

Yulun Wu, Doron Bergman

Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization

Yang Chen, Long Yang, Yitao Liang et al.

Optimizing Language Models for Inference Time Objectives using Reinforcement Learning

Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve et al.

Telling Peer Direct Effects from Indirect Effects in Observational Network Data

Xiaojing Du, Jiuyong Li, Debo Cheng et al.

Active feature acquisition via explainability-driven ranking

Osman Berke Guney, Ketan Saichandran, Karim Elzokm et al.

Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain

Gaozheng Pei, Ke Ma, Yingfei Sun et al.

Hyper-Transforming Latent Diffusion Models

Ignacio Peis, Batuhan Koyuncu, Isabel Valera et al.

SpikF: Spiking Fourier Network for Efficient Long-term Prediction

Wenjie Wu, Dexuan Huo, Hong Chen

Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics

Haoming Jing, Yorie Nakahira

Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes

Zhuocheng Gong, Jian Guan, Wei Wu et al.

BILBO: BILevel Bayesian Optimization

Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low

Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing

Han Jiang, Xiaoyuan Yi, Zhihua Wei et al.

Taming Knowledge Conflicts in Language Models

Gaotang Li, Yuzhong Chen, Hanghang Tong

Decoupled SGDA for Games with Intermittent Strategy Communication

Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.

Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs

Jie Hu, Yi-Ting Ma, Do-Young Eun

CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging

Zongzhen Yang, Binhang Qi, Hailong Sun et al.

Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations

Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.

MindAligner: Explicit Brain Functional Alignment for Cross-Subject Visual Decoding from Limited fMRI Data

Yuqin Dai, Zhouheng Yao, Chunfeng Song et al.

You Get What You Give: Reciprocally Fair Federated Learning

Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.