Most Cited ICML "data markets" Papers
5,975 papers found • Page 11 of 30
Conference
GraphCL: Graph-based Clustering for Semi-Supervised Medical Image Segmentation
Mengzhu Wang, houcheng su, Jiao Li et al.
Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
Anqi Mao, Mehryar Mohri, Yutao Zhong
Benchmarking Quantum Reinforcement Learning
Nico Meyer, Christian Ufrecht, George Yammine et al.
Unified Breakdown Analysis for Byzantine Robust Gossip
Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
Memory Efficient Neural Processes via Constant Memory Attention Block
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
Differentiable Distributionally Robust Optimization Layers
Xutao Ma, Chao Ning, WenLi Du
Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization
Zelai Xu, Wanjun Gu, Chao Yu et al.
Bayesian Design Principles for Offline-to-Online Reinforcement Learning
Hao Hu, yiqin yang, Jianing Ye et al.
Secant Line Search for Frank-Wolfe Algorithms
Deborah Hendrych, Sebastian Pokutta, Mathieu Besançon et al.
Proto Successor Measure: Representing the Behavior Space of an RL Agent
Siddhant Agarwal, Harshit Sikchi, Peter Stone et al.
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai et al.
DCBM: Data-Efficient Visual Concept Bottleneck Models
Katharina Prasse, Patrick Knab, Sascha Marton et al.
C-3PO: Compact Plug-and-Play Proxy Optimization to Achieve Human-like Retrieval-Augmented Generation
Guoxin Chen, Minpeng Liao, Peiying Yu et al.
Hierarchical Graph Tokenization for Molecule-Language Alignment
Yongqiang Chen, QUANMING YAO, Juzheng Zhang et al.
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
Chendi Wang, Yuqing Zhu, Weijie Su et al.
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao et al.
ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think
Tao Feng, Wei Li, Didi Zhu et al.
UniDB: A Unified Diffusion Bridge Framework via Stochastic Optimal Control
Kaizhen Zhu, Mokai Pan, Yuexin Ma et al.
Discrete Neural Algorithmic Reasoning
Gleb Rodionov, Liudmila Prokhorenkova
Privacy Attacks on Image AutoRegressive Models
Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch et al.
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization
Songhua Liu, Xin Jin, Xingyi Yang et al.
ROPO: Robust Preference Optimization for Large Language Models
Xize Liang, Chao Chen, Shuang Qiu et al.
ReferSplat: Referring Segmentation in 3D Gaussian Splatting
Shuting He, Guangquan Jie, Changshuo Wang et al.
Denoising Autoregressive Representation Learning
Yazhe Li, Jorg Bornschein, Ting Chen
Recovering Labels from Local Updates in Federated Learning
Huancheng Chen, Haris Vikalo
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
GRATH: Gradual Self-Truthifying for Large Language Models
Weixin Chen, Dawn Song, Bo Li
LensLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Xinyue Zeng, Haohui Wang, Junhong Lin et al.
Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion
Tianyuan Zou, Yang Liu, Peng Li et al.
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
Clément Bonet, Christophe Vauthier, Anna Korba
Bagged Deep Image Prior for Recovering Images in the Presence of Speckle Noise
Xi Chen, Zhewen Hou, Christopher Metzler et al.
Exponential Family Variational Flow Matching for Tabular Data Generation
Andres Guzman Cordero, Floor Eijkelboom, Jan-Willem van de Meent
How to Leverage Diverse Demonstrations in Offline Imitation Learning
Sheng Yue, Jiani Liu, Xingyuan Hua et al.
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu et al.
Doubly Robust Conformalized Survival Analysis with Right-Censored Data
Matteo Sesia, vladimir svetnik
TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference
Jack Min Ong, Matthew Di Ferrante, Aaron Pazdera et al.
Limitations of measure-first protocols in quantum machine learning
Casper Gyurik, Riccardo Molteni, Vedran Dunjko
EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
Oliver Sieberling, Denis Kuznedelev, Eldar Kurtic et al.
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
Zhining Liu, Ze Yang, Xiao Lin et al.
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model
Umberto Tomasini, Matthieu Wyart
Aligning Spoken Dialogue Models from User Interactions
Anne Wu, Laurent Mazaré, Neil Zeghidour et al.
Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations
Shahaf Bassan, Yizhak Elboher, Tobias Ladner et al.
WOMD-Reasoning: A Large-Scale Dataset for Interaction Reasoning in Driving
Yiheng Li, Cunxin Fan, Chongjian GE et al.
Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms
Filippo Lazzati, Mirco Mutti, Alberto Maria Metelli
Post-hoc Part-Prototype Networks
Andong Tan, Fengtao ZHOU, Hao Chen
Single-Model Attribution of Generative Models Through Final-Layer Inversion
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer et al.
Retraining-free Merging of Sparse MoE via Hierarchical Clustering
I-Chun Chen, Hsu-Shen Liu, Wei-Fang Sun et al.
Auto-Linear Phenomenon in Subsurface Imaging
Yinan Feng, Yinpeng Chen, Peng Jin et al.
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
Haoyang Zheng, Hengrong Du, Qi Feng et al.
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
Arjun Subramonian, Levent Sagun, Yizhou Sun
Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning
Guozheng Ma, Lu Li, Zilin Wang et al.
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang et al.
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
EasyInv: Toward Fast and Better DDIM Inversion
Ziyue Zhang, Mingbao Lin, Shuicheng YAN et al.
Private Federated Learning using Preference-Optimized Synthetic Data
Charlie Hou, Mei-Yu Wang, Yige Zhu et al.
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
Sungyoon Kim, Mert Pilanci
Kinetic Langevin Diffusion for Crystalline Materials Generation
François Cornet, Federico Bergamin, Arghya Bhowmik et al.
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li, Jingdong Zhang, Qunxi Zhu et al.
Layerwise Change of Knowledge in Neural Networks
Xu Cheng, Lei Cheng, Zhaoran Peng et al.
Protein Structure Tokenization: Benchmarking and New Recipe
Xinyu Yuan, Zichen Wang, Marcus Collins et al.
Gaussian Plane-Wave Neural Operator for Electron Density Estimation
Seongsu Kim, Sungsoo Ahn
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
Amutheezan Sivagnanam, Ava Pettet, Hunter Lee et al.
Tell, Don't Show: Language Guidance Eases Transfer Across Domains in Images and Videos
Tarun Kalluri, Bodhisattwa Prasad Majumder, Manmohan Chandraker
Language Generation with Strictly Proper Scoring Rules
Chenze Shao, Fandong Meng, Yijin Liu et al.
Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
Jingfeng Wu, Peter Bartlett, Matus Telgarsky et al.
Relational DNN Verification With Cross Executional Bound Refinement
Debangshu Banerjee, Gagandeep Singh
VCT: Training Consistency Models with Variational Noise Coupling
Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai et al.
ReLUs Are Sufficient for Learning Implicit Neural Representations
Joseph Shenouda, Yamin Zhou, Robert Nowak
Emergent Response Planning in LLMs
Zhichen Dong, Zhanhui Zhou, Zhixuan Liu et al.
Random features models: a way to study the success of naive imputation
Alexis Ayme, Claire Boyer, Aymeric Dieuleveut et al.
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Simultaneous identification of models and parameters of scientific simulators
Cornelius Schröder, Jakob Macke
Do Transformer World Models Give Better Policy Gradients?
Michel Ma, Tianwei Ni, Clement Gehring et al.
What Makes a Good Feedforward Computational Graph?
Alex Vitvitskyi, João Madeira Araujo, Marc Lackenby et al.
STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings
Saksham Rastogi, Pratyush Maini, Danish Pruthi
Provable Maximum Entropy Manifold Exploration via Diffusion Models
Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh et al.
Constrained Ensemble Exploration for Unsupervised Skill Discovery
Chenjia Bai, Rushuai Yang, Qiaosheng Zhang et al.
Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning
Liang CHEN, Xueting Han, Li Shen et al.
On the Identifiability of Switching Dynamical Systems
Carles Balsells-Rodas, Yixin Wang, Yingzhen Li
Learning Adaptive Lighting via Channel-Aware Guidance
Qirui Yang, Peng-Tao Jiang, Hao Zhang et al.
Componential Prompt-Knowledge Alignment for Domain Incremental Learning
Kunlun Xu, Xu Zou, Gang Hua et al.
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction
Chen-Yu Yen, raghav singhal, Umang Sharma et al.
Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
Jie Bao, Chuangyin Dang, Rui Luo et al.
Adaptive Learning of Density Ratios in RKHS
Werner Zellinger, Stefan Kindermann, Sergei V. Pereverzyev
Invariant Risk Minimization Is A Total Variation Model
Zhao-Rong Lai, Weiwen Wang
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Ye Tian, Haolei Weng, Yang Feng
Aligning Protein Conformation Ensemble Generation with Physical Feedback
Jiarui Lu, Xiaoyin Chen, Stephen Lu et al.
Universal Gradient Methods for Stochastic Convex Optimization
Anton Rodomanov, Ali Kavis, Yongtao Wu et al.
Hyperband-based Bayesian Optimization for Black-box Prompt Selection
Lennart Schneider, Martin Wistuba, Aaron Klein et al.
Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed
Savelii Chezhegov, Klyukin Yaroslav, Andrei Semenov et al.
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras et al.
Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity
Erpai Luo, Xinran Wei, Lin Huang et al.
QT-DoG: Quantization-Aware Training for Domain Generalization
Saqib Javed, Hieu Le, Mathieu Salzmann
Implicit meta-learning may lead language models to trust more reliable sources
Dmitrii Krasheninnikov, Egor Krasheninnikov, Bruno Mlodozeniec et al.
Enhancing Target-unspecific Tasks through a Features Matrix
Fangming Cui, Yonggang Zhang, Xuan Wang et al.
Cross-domain Open-world Discovery
Shuo Wen, Maria Brbic
Infinite-Horizon Distributionally Robust Regret-Optimal Control
Taylan Kargin, Joudi Hajar, Vikrant Malik et al.
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong et al.
Trajectory Inference with Smooth Schrödinger Bridges
Wanli Hong, Yuliang Shi, Jonathan Niles-Weed
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
Yi Yu, Song Xia, SIYUAN YANG et al.
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen et al.
The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions
Wenbo Pan, Zhichao Liu, Qiguang Chen et al.
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm
Fuzhong Zhou, Chenyu Zhang, Xu Chen et al.
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
Yuecheng Li, Lele Fu, Tong Wang et al.
BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
Yunlong Hou, Fengzhuo Zhang, Cunxiao Du et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
Yu Zhang, Qi Zhang, Zixuan Gong et al.
Fast Text-to-3D-Aware Face Generation and Manipulation via Direct Cross-modal Mapping and Geometric Regularization
Jinlu Zhang, Yiyi Zhou, Qiancheng Zheng et al.
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng et al.
Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning
Hongming Zhang, Tongzheng Ren, Chenjun Xiao et al.
Prospective Side Information for Latent MDPs
Jeongyeol Kwon, Yonathan Efroni, Shie Mannor et al.
Detecting and Identifying Selection Structure in Sequential Data
Yujia Zheng, Zeyu Tang, Yiwen Qiu et al.
Understanding and Diagnosing Deep Reinforcement Learning
Ezgi Korkmaz
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
Emilia Magnani, Marvin Pförtner, Tobias Weber et al.
Bivariate Causal Discovery using Bayesian Model Selection
Anish Dhir, Samuel Power, Mark van der Wilk
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
Jiacheng Zhang, Feng Liu, Dawei Zhou et al.
Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation
Fengdi Che, Chenjun Xiao, Jincheng Mei et al.
ILILT: Implicit Learning of Inverse Lithography Technologies
Haoyu Yang, Mark Ren
Learning Distances from Data with Normalizing Flows and Score Matching
Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr et al.
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
SlimLLM: Accurate Structured Pruning for Large Language Models
Jialong Guo, Xinghao Chen, Yehui Tang et al.
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
Parand A. Alamdari, Toryn Q. Klassen, Elliot Creager et al.
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses
Panagiotis Koromilas, Giorgos Bouritsas, Theodoros Giannakopoulos et al.
On the Robustness of Reward Models for Language Model Alignment
Jiwoo Hong, Noah Lee, Eunki Kim et al.
Independence Tests for Language Models
Sally Zhu, Ahmed Ahmed, Rohith Kuditipudi et al.
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks
Tuomas Oikarinen, Ge Yan, Lily Weng
Efficient Distributed Optimization under Heavy-Tailed Noise
Su Hyeong Lee, Manzil Zaheer, Tian Li
Sub-token ViT Embedding via Stochastic Resonance Transformers
Dong Lao, Yangchao Wu, Tian Yu Liu et al.
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
Max Wilcoxson, Qiyang Li, Kevin Frans et al.
Model Assessment and Selection under Temporal Distribution Shift
Elise Han, Chengpiao Huang, Kaizheng Wang
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Zhitong Xu, Da Long, Yiming Xu et al.
Aligning LLMs by Predicting Preferences from User Writing Samples
Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald et al.
On the Nonlinearity of Layer Normalization
Yunhao Ni, Yuxin Guo, Junlong Jia et al.
Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks
Arjun Karuvally, Terrence Sejnowski, Hava Siegelmann
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations
Henrik Schopmans, Pascal Friederich
On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization
Motahareh Sohrabi, Juan Ramirez, Tianyue Zhang et al.
Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups
Weiqiu You, Helen Qu, Marco Gatti et al.
DOLPHIN: A Programmable Framework for Scalable Neurosymbolic Learning
Aaditya Naik, Jason Liu, Claire Wang et al.
TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
Hyeongwon Jang, Changhun Kim, Eunho Yang
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks
Etienne Boursier, Nicolas Flammarion
Shielded Diffusion: Generating Novel and Diverse Images using Sparse Repellency
Michael Kirchhof, James Thornton, Louis Béthune et al.
Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding
Ziyao Wang, Muneeza Azmat, Ang Li et al.
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
Hyeongjin Kim, Sangwon Kim, Dasom Ahn et al.
Robust and Conjugate Spatio-Temporal Gaussian Processes
William Laplante, Matias Altamirano, Andrew Duncan et al.
Controlled Generation with Equivariant Variational Flow Matching
Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama et al.
Encodings for Prediction-based Neural Architecture Search
Yash Akhauri, Mohamed Abdelfattah
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling
Alexander Capstick, Rahul G. Krishnan, Payam Barnaghi
FOUNDER: Grounding Foundation Models in World Models for Open-Ended Embodied Decision Making
Yucen Wang, Rui Yu, Shenghua Wan et al.
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation
Yibo Yang, Xiaojie Li, Motasem Alfarra et al.
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin et al.
LASER: Linear Compression in Wireless Distributed Optimization
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels et al.
Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
Qianglin Wen, Chengchun Shi, Ying Yang et al.
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
Ziping Ma, Furong Xu, Jian liu et al.
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-chan Tien, Peng Ding et al.
Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better
Vicente Balmaseda, Ying Xu, Yixin Cao et al.
On the Hardness of Probabilistic Neurosymbolic Learning
Jaron Maene, Vincent Derkinderen, Luc De Raedt
Scaling Laws for Upcycling Mixture-of-Experts Language Models
Seng Pei Liew, Takuya Kato, Sho Takase
The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
Walter Mayor, Johan Obando-Ceron, Aaron Courville et al.
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations
Paarth Neekhara, Shehzeen Hussain, Rafael Valle et al.
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun et al.
Variational Control for Guidance in Diffusion Models
Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler et al.
Evaluation of Test-Time Adaptation Under Computational Time Constraints
Motasem Alfarra, Hani Itani, Alejandro Pardo et al.
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Lanxiang Xing, Haixu Wu, yuezhou ma et al.
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
Yu Luo, Tianying Ji, Fuchun Sun et al.
Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Control
Zheng Xiong, Risto Vuorio, Jacob Beck et al.
Ultra-Resolution Adaptation with Ease
Ruonan Yu, Songhua Liu, Zhenxiong Tan et al.
Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design
Shuze Liu, Shangtong Zhang
OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
Bin Lu, Ze Zhao, Luyu Han et al.
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith Mills et al.
Language Models over Canonical Byte-Pair Encodings
Tim Vieira, Tianyu Liu, Clemente Pasti et al.
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
Amine Ouasfi, Adnane Boukhayma
Optimal Differentially Private Model Training with Public Data
Andrew Lowy, Zeman Li, Tianjian Huang et al.
Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
Mingqing Xiao, Yixin Zhu, Di He et al.
Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning
Mohamed Elsayed, Homayoon Farrahi, Felix Dangel et al.
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise
Thomas Pouplin, Alan Jeffares, Nabeel Seedat et al.
Position: The Most Expensive Part of an LLM *should* be its Training Data
Nikhil Kandpal, Colin Raffel
Mitigating Label Noise on Graphs via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia et al.
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin et al.
ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
Yuanchao Xu, Kaidi Shao, Nikos Logothetis et al.
Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi et al.
Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
Chendi Ge, Xin Wang, Zeyang Zhang et al.
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
Yuancheng Xu, Chenghao Deng, Yanchao Sun et al.
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
Towards Robustness and Explainability of Automatic Algorithm Selection
Xingyu Wu, Jibin Wu, Yu Zhou et al.
EEG-Language Pretraining for Highly Label-Efficient Clinical Phenotyping
Sam Gijsen, Kerstin Ritter
Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences
Yunhong Lu, Qichao Wang, Hengyuan Cao et al.
Auditing Prompt Caching in Language Model APIs
Chenchen Gu, Xiang Li, Rohith Kuditipudi et al.
Physics-Informed Generative Modeling of Wireless Channels
Benedikt Böck, Andreas Oeldemann, Timo Mayer et al.
Learning Pseudo-Contractive Denoisers for Inverse Problems
Deliang Wei, Peng Chen, Fang Li
Is Complex Query Answering Really Complex?
Cosimo Gregucci, Bo Xiong, Daniel Hernández et al.
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
Efficient Algorithms for Sum-Of-Minimum Optimization
Lisang Ding, Ziang Chen, Xinshang Wang et al.
Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features
Thalles Silva, Helio Pedrini, Adín Ramírez Rivera