Most Cited ICML "composed image retrieval" Papers
5,975 papers found • Page 8 of 30
Conference
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition
Sungnyun Kim, Kangwook Jang, Sangmin Bae et al.
SynEVO: A neuro-inspired spatiotemporal evolutional framework for cross-domain adaptation
jiayue Liu, Zhongchao Yi, Zhengyang Zhou et al.
Ranked from Within: Ranking Large Multimodal Models Without Labels
Weijie Tu, Weijian Deng, Dylan Campbell et al.
Knowledge Retention in Continual Model-Based Reinforcement Learning
Haotian Fu, Yixiang Sun, Michael L. Littman et al.
Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
junmin zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian et al.
Adaptive Sample Sharing for Multi Agent Linear Bandits
Hamza Cherkaoui, Merwan Barlier, Igor Colin
Synthetic Text Generation for Training Large Language Models via Gradient Matching
Dang Nguyen, Zeman Li, MohammadHossein Bateni et al.
Dual Feature Reduction for the Sparse-group Lasso and its Adaptive Variant
Fabio Feser, Marina Evangelou
Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
Anqi Mao, Mehryar Mohri, Yutao Zhong
The Limits of Predicting Agents from Behaviour
Alexis Bellot, Jonathan Richens, Tom Everitt
Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism
Aviv Bick, Eric Xing, Albert Gu
Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory
Mason O. Smith, Wenlong Zhang
Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla
Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spaces
Henry Moss, Sebastian Ober, Tom Diethe
SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding
Woohyeon Park, Woojin Kim, Jaeik Kim et al.
Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff et al.
Maximizing Intermediate Checkpoint Value in LLM Pretraining with Bayesian Optimization
Deyuan Liu, Zecheng Wang, Bingning Wang et al.
BSO: Binary Spiking Online Optimization Algorithm
Yu Liang, Yu Yang, Wenjie Wei et al.
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance
Guoqing Chao, Zhenghao Zhang, Lei Meng et al.
The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport
Chenrui Wang, Yixuan Qiu
Compositional Condition Question Answering in Tabular Understanding
Jun-Peng Jiang, Tao Zhou, De-Chuan Zhan et al.
Contradiction Retrieval via Contrastive Learning with Sparsity
Haike Xu, Zongyu Lin, Kai-Wei Chang et al.
Textual Unlearning Gives a False Sense of Unlearning
Jiacheng Du, Zhibo Wang, Jie Zhang et al.
Offline Learning for Combinatorial Multi-armed Bandits
Xutong Liu, Xiangxiang Dai, Jinhang Zuo et al.
HyperIV: Real-time Implied Volatility Smoothing
Yongxin Yang, Wenqi Chen, Chao Shu et al.
SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
Haoquan Fang, Markus Grotz, Wilbert Pumacay et al.
FLAM: Frame-Wise Language-Audio Modeling
Yusong Wu, Christos Tsirigotis, Ke Chen et al.
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems
Botao Chen, Jongyeong Lee, Junya Honda
Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
Yuan Xin, Dingfan Chen, Michael Backes et al.
Splitting & Integrating: Out-of-Distribution Detection via Adversarial Gradient Attribution
Jiayu Zhang, Xinyi Wang, Zhibo Jin et al.
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin et al.
A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
Kihyuk Hong, Ambuj Tewari
SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
Yong Liu, Di Fu, Shenggan Cheng et al.
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.
The Price of Linear Time: Error Analysis of Structured Kernel Interpolation
Alexander Moreno, Justin Xiao, Jonathan Mei
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le Tuyet Nhi PHAM, Dario Shariatian, Antonio Ocello et al.
Compositional Risk Minimization
Divyat Mahajan, Mohammad Pezeshki, Charles Arnal et al.
Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu et al.
ROME is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck
Zheng Zhou, Wenquan Feng, Qiaosheng Zhang et al.
Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks
Jincheng Huang, Yujie Mo, Xiaoshuang Shi et al.
Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning
Wenke Huang, Jian Liang, Guancheng Wan et al.
Drug-TTA: Test-Time Adaptation for Drug Virtual Screening via Multi-task Meta-Auxiliary Learning
Ao Shen, Ming'zhi Yuan, Yingfan MA et al.
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Li, Daohan Lu, Polina Kirichenko et al.
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Multi-View Graph Clustering via Node-Guided Contrastive Encoding
Yazhou Ren, Junlong Ke, Zichen Wen et al.
Calibrating Video Watch-time Predictions with Credible Prototype Alignment
Chao, Shisong Tang, Fan Li et al.
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han, Mengmi Zhang
Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning
Motoki Omura, Kazuki Ota, Takayuki Osa et al.
STAIR: Improving Safety Alignment with Introspective Reasoning
Yichi Zhang, Siyuan Zhang, Yao Huang et al.
Training Dynamics of In-Context Learning in Linear Attention
Yedi Zhang, Aaditya Singh, Peter Latham et al.
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber et al.
Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation
Juncheol Shin, Minsang Seok, Seonggon Kim et al.
Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
Ruichuan Huang, Jiawei Zhang, Ahmet Alacaoglu
Flow-field inference from neural data using deep recurrent networks
Timothy Doyeon Kim, Thomas Luo, Tankut Can et al.
Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
Yucheng Hu, Yanjiang Guo, Pengchao Wang et al.
CoCoA-Mix: Confusion-and-Confidence-Aware Mixture Model for Context Optimization
Dasol Hong, Wooju Lee, Hyun Myung
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams
Lin Zhu, Xiantao Ma, Xiao Wang et al.
Learning Fused State Representations for Control from Multi-View Observations
Zeyu Wang, Yao-Hui Li, Xin Li et al.
Curse of High Dimensionality Issue in Transformer for Long Context Modeling
Shuhai Zhang, Zeng You, Yaofo Chen et al.
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
Joshua Southern, Yam Eitan, Guy Bar Shalom et al.
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
Ju-Seung Byun, Andrew Perrault
Revisiting Non-Acyclic GFlowNets in Discrete Environments
Nikita Morozov, Ian Maksimov, Daniil Tiapkin et al.
Large Language Models to Diffusion Finetuning
Edoardo Cetin, Tianyu Zhao, Yujin Tang
Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks
Sungwon Kim, Namkyeong Lee, Yunyoung Doh et al.
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida et al.
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks
Dongwoo Lee, Dong Bok Lee, Steven Adriaensen et al.
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
Global curvature for second-order optimization of neural networks
Alberto Bernacchia
Large Continual Instruction Assistant
Jingyang Qiao, zhizhong zhang, Xin Tan et al.
K$^2$IE: Kernel Method-based Kernel Intensity Estimators for Inhomogeneous Poisson Processes
Hideaki Kim, Tomoharu Iwata, Akinori Fujino
A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations
Junwei Su, Chuan Wu
Retrieval-Augmented Perception: High-resolution Image Perception Meets Visual RAG
Wenbin Wang, Yongcheng Jing, Liang Ding et al.
Unsupervised Learning for Class Distribution Mismatch
Pan Du, Zhao, Xinai Lu et al.
Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling
Shuqi Lu, Xiaohong Ji, Bohang Zhang et al.
Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
Gabriele Visentin, Patrick Cheridito
InfoCons: Identifying Interpretable Critical Concepts in Point Clouds via Information Theory
Feifei Li, Mi Zhang, Zhaoxiang Wang et al.
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.
A Model of Place Field Reorganization During Reward Maximization
M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth et al.
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
Sample-Optimal Agnostic Boosting with Unlabeled Data
Udaya Ghai, Karan Singh
Boosting Adversarial Robustness with CLAT: Criticality Leveraged Adversarial Training
Bhavna Gopal, Huanrui Yang, Jingyang Zhang et al.
AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism
Zhepei Wei, Wei-Lin Chen, Xinyu Zhu et al.
PF3plat: Pose-Free Feed-Forward 3D Gaussian Splatting for Novel View Synthesis
Sunghwan Hong, Jaewoo Jung, Heeseong Shin et al.
Conservative Offline Goal-Conditioned Implicit V-Learning
Ke Kaiqiang, qian lin, Zongkai Liu et al.
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving Regularization
Ziyu Gong, Jim Lim, David I. Inouye
SkipGPT: Each Token is One of a Kind
Anhao Zhao, Fanghua Ye, Yingqi Fan et al.
Scalable Approximation Algorithms for $p$-Wasserstein Distance and Its Variants
Nathaniel Lahn, Sharath Raghvendra, Emma Saarinen et al.
OmniArch: Building Foundation Model for Scientific Computing
Tianyu Chen, Haoyi Zhou, Ying Li et al.
Improving Out-of-Distribution Detection via Dynamic Covariance Calibration
Kaiyu Guo, Zijian Wang, Tan Pan et al.
Self-Consuming Generative Models with Adversarially Curated Data
Xiukun Wei, Xueru Zhang
Fast, Accurate Manifold Denoising by Tunneling Riemannian Optimization
Shiyu Wang, Mariam Avagyan, Yihan Shen et al.
Super Deep Contrastive Information Bottleneck for Multi-modal Clustering
Zhengzheng Lou, Ke Zhang, Yucong Wu et al.
Sleeping Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
LongRoPE2: Near-Lossless LLM Context Window Scaling
Ning Shang, Li Lyna Zhang, Siyuan Wang et al.
Trusted Multi-View Classification with Expert Knowledge Constraints
Xinyan Liang, Shijie Wang, Yuhua Qian et al.
Statistical Test for Feature Selection Pipelines by Selective Inference
Tomohiro Shiraishi, Tatsuya Matsukawa, Shuichi Nishino et al.
A Unified Framework for Generalization Error Analysis of Learning with Arbitrary Discrete Weak Features
Kosuke Sugiyama, Masato Uchida
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.
One-Step Generalization Ratio Guided Optimization for Domain Generalization
Sumin Cho, Dongwon Kim, Kwangsu Kim
Discovering Symbolic Cognitive Models from Human and Animal Behavior
Pablo Samuel Castro, Nenad Tomasev, Ankit Anand et al.
TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization
Songtao Lu
Adapting Precomputed Features for Efficient Graph Condensation
Yuan Li, Jun Hu, Zemin Liu et al.
General agents need world models
Jonathan Richens, Tom Everitt, David Abel
Learning Latent Graph Structures and their Uncertainty
Alessandro Manenti, Daniele Zambon, Cesare Alippi
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
Yuanchao Xu, Kaidi Shao, Nikos Logothetis et al.
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Towards Cost-Effective Reward Guided Text Generation
Ahmad Rashid, Ruotian Wu, Rongqi Fan et al.
Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering
Zihan Song, Xin Wang, Zi Qian 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
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search
Haoran Luo, Haihong E, Yikai Guo et al.
Cross-City Latent Space Alignment for Consistency Region Embedding
Meng Chen, Hongwei Jia, Zechen Li et al.
Can Biologically Plausible Temporal Credit Assignment Rules Match BPTT for Neural Similarity? E-prop as an Example
Yuhan Helena Liu, Guangyu Robert Yang, Christopher Cueva
Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback
Zihan Zhang, Yuxin Chen, Jason Lee et al.
Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
Kei Sen Fong, Mehul Motani
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
Tyler Kastner, Mark Rowland, Yunhao Tang et al.
Hidden No More: Attacking and Defending Private Third-Party LLM Inference
Rahul Thomas, Louai Zahran, Erica Choi et al.
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.
Star Attention: Efficient LLM Inference over Long Sequences
Shantanu Acharya, Fei Jia, Boris Ginsburg
Understanding the Logic of Direct Preference Alignment through Logic
Kyle Richardson, Vivek Srikumar, Ashish Sabharwal
Evolving Minds: Logic-Informed Inference from Temporal Action Patterns
Chao Yang, Shuting Cui, Yang Yang et al.
RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
Xinnuo Xu, Rachel Lawrence, Kshitij Dubey et al.
Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints
Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
Jiachen Hu, Rui Ai, Han Zhong et al.
Semantics-aware Test-time Adaptation for 3D Human Pose Estimation
Qiuxia Lin, Glory Rongyu CHEN, Kerui Gu et al.
Steering Protein Language Models
Long-Kai Huang, Rongyi Zhu, Bing He et al.
Compact Matrix Quantum Group Equivariant Neural Networks
Edward Pearce-Crump
Channel Normalization for Time Series Channel Identification
Seunghan Lee, Taeyoung Park, Kibok Lee
Synthesizing Software Engineering Data in a Test-Driven Manner
Lei Zhang, Jiaxi Yang, Min Yang et al.
Hypothesis Testing for Generalized Thurstone Models
Anuran Makur, Japneet Singh
Reinforced Learning Explicit Circuit Representations for Quantum State Characterization from Local Measurements
Manwen Liao, Yan Zhu, Weitian Zhang et al.
Deep Neural Cellular Potts Models
Koen Minartz, Tim d'Hondt, Leon Hillmann et al.
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.
OmniAudio: Generating Spatial Audio from 360-Degree Video
Huadai Liu, Tianyi Luo, Kaicheng Luo 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.
An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective
Xinyue Chen, Jinfeng Peng, Yuhao Li et al.
Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
Nate Veldt, Thomas Stanley, Benjamin Priest et al.
High Probability Bound for Cross-Learning Contextual Bandits with Unknown Context Distributions
Ruiyuan Huang, Zengfeng Huang
TeDS: Joint Learning of Diachronic and Synchronic Perspectives in Quaternion Space for Temporal Knowledge Graph Completion
Jiujiang Guo, Mankun Zhao, Wenbin Zhang et al.
Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
Hengquan Guo, Lingkai Zu, Xin Liu
MERIT: Maximum-normalized Element-wise Ratio for Language Model Large-batch Training
Yang Luo, Zangwei Zheng, Ziheng Qin et al.
Equivariant Polynomial Functional Networks
Thieu Vo, Viet Hoang Tran, Tho Tran Huu et al.
MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
Jeffrey A. Chan-Santiago, praveen tirupattur, Gaurav Kumar Nayak et al.
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr 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.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
ABNet: Adaptive explicit-Barrier Net for Safe and Scalable Robot Learning
Wei Xiao, Johnson Tsun-Hsuan Wang, Chuang Gan et al.
Scaling Sparse Feature Circuits For Studying In-Context Learning
Dmitrii Kharlapenko, Stepan Shabalin, Arthur Conmy et al.
Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction
Ankit Ghosh, Gargee Kashyap, Sarthak Mittal et al.
Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance Learning
Boyuan Wu, wang, Xianwei Lin et al.
Towards Better-than-2 Approximation for Constrained Correlation Clustering
Andreas Kalavas, Evangelos Kipouridis, Nithin Varma
Bayesian Inference for Correlated Human Experts and Classifiers
Markelle Kelly, Alex Boyd, Samuel Showalter et al.
Do NOT Think That Much for 2+3=? On the Overthinking of Long Reasoning Models
Xingyu Chen, Jiahao Xu, Tian Liang et al.
Heterogeneous Sufficient Dimension Reduction and Subspace Clustering
Lei Yan, Xin Zhang, Qing Mai
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Shen et al.
LLMs Can Reason Faster Only If We Let Them
Bilgehan Sel, Lifu Huang, Naren Ramakrishnan et al.
Provable Policy Gradient for Robust Average-Reward MDPs Beyond Rectangularity
Qiuhao Wang, Yuqi Zha, Chin Pang Ho et al.
IT$^3$: Idempotent Test-Time Training
Nikita Durasov, Assaf Shocher, Doruk Oner et al.
Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark
Yunzhuo Hao, Jiawei Gu, Huichen Wang et al.
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertainty
Harry Zhang, Luca Carlone
When and How Does CLIP Enable Domain and Compositional Generalization?
Elias Kempf, Simon Schrodi, Max Argus et al.
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
Sho Takemori, Yuhei Umeda, Aditya Gopalan
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
Curvature-aware Graph Attention for PDEs on Manifolds
Yunfeng Liao, Jiawen Guan, Xiucheng Li
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan et al.
Certification for Differentially Private Prediction in Gradient-Based Training
Matthew Wicker, Philip Sosnin, Igor Shilov 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.
Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
Sheheryar Mehmood, Peter Ochs
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant 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
Vector Grimoire: Codebook-based Shape Generation under Raster Image Supervision
Marco Cipriano, Moritz Feuerpfeil, Gerard de Melo
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
Nonparametric Modern Hopfield Models
Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu et al.
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani 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
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre 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.
Contour Integration Underlies Human-Like Vision
Ben Lonnqvist, Elsa Scialom, Abdulkadir Gokce et al.
Generative Point Cloud Registration
Haobo Jiang, Jin Xie, jian Yang 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.
Cross-environment Cooperation Enables Zero-shot Multi-agent Coordination
Kunal Jha, Wilka Carvalho, Yancheng Liang et al.
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
WildChat-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Benjamin Feuer, Chinmay Hegde