Most Cited ICLR "incentive compatibility" Papers
6,124 papers found • Page 31 of 31
Conference
Variational Bayesian Last Layers
James Harrison, John Willes, Jasper Snoek
IDEAL: Influence-Driven Selective Annotations Empower In-Context Learners in Large Language Models
Shaokun Zhang, Xiaobo Xia, Zhaoqing Wang et al.
Efficient local linearity regularization to overcome catastrophic overfitting
Elias Abad Rocamora, Fanghui Liu, Grigorios Chrysos et al.
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto et al.
A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
Erdun Gao, Howard Bondell, Wei Huang et al.
DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS
Ilan Price, Nicholas Daultry Ball, Adam Jones et al.
A Foundation Model for Error Correction Codes
Yoni Choukroun, Lior Wolf
Learning to Make Adherence-aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun et al.
Tree Search-Based Policy Optimization under Stochastic Execution Delay
David Valensi, Esther Derman, Shie Mannor et al.
Sufficient conditions for offline reactivation in recurrent neural networks
Nanda H Krishna, Colin Bredenberg, Daniel Levenstein et al.
Memory-Consistent Neural Networks for Imitation Learning
Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman et al.
Fusing Models with Complementary Expertise
Hongyi Wang, Felipe Polo, Yuekai Sun et al.
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
Zecheng Wang, Che Wang, Zixuan Dong et al.
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization
Yuhang Zang, Hanlin Goh, Joshua Susskind et al.
Reinforcement Symbolic Regression Machine
Yilong Xu, Yang Liu, Hao Sun
BRUSLEATTACK: A QUERY-EFFICIENT SCORE- BASED BLACK-BOX SPARSE ADVERSARIAL ATTACK
Quoc Viet Vo, Ehsan Abbasnejad, Damith Ranasinghe
First-order ANIL provably learns representations despite overparametrisation
Oğuz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Chong Mou, Xintao Wang, Jiechong Song et al.
Task Planning for Visual Room Rearrangement under Partial Observability
Karan Mirakhor, Sourav Ghosh, DIPANJAN DAS et al.
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Yulu Gan, Sung Woo Park, Alexander Schubert et al.
3D Reconstruction with Generalizable Neural Fields using Scene Priors
Yang Fu, Shalini De Mello, Xueting Li et al.
LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
Xin Liu, Muhammad Khalifa, Lu Wang
Massive Editing for Large Language Models via Meta Learning
Chenmien Tan, Ge Zhang, Jie Fu
Fantastic Generalization Measures are Nowhere to be Found
Michael Gastpar, Ido Nachum, Jonathan Shafer et al.
VeRA: Vector-based Random Matrix Adaptation
Dawid Kopiczko, Tijmen Blankevoort, Yuki Asano
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
Changwen Zhang, wenli ouyang, Hao Yuan et al.
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
Robert Peach, Matteo Vinao-Carl, Nir Grossman et al.
PeFLL: Personalized Federated Learning by Learning to Learn
Jonathan Scott, Hossein Zakerinia, Christoph Lampert
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Guowei Xu, Ruijie Zheng, Yongyuan Liang et al.
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
Yuan Liu, Cheng Lin, Zijiao Zeng et al.
Learning dynamic representations of the functional connectome in neurobiological networks
Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley et al.
Learning interpretable control inputs and dynamics underlying animal locomotion
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin et al.
The Effectiveness of Random Forgetting for Robust Generalization
Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe Arani
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit, Liangze Jiang, Andrei Atanov et al.
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
Liyiming Ke, Yunchu Zhang, Abhay Deshpande et al.
Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
Khalid OUBLAL, Said Ladjal, David Benhaiem et al.
GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules
Zhenfang Chen, Rui Sun, Wenjun Liu et al.
Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models
Yingtao Zhang, Haoli Bai, Haokun Lin et al.
Learning to Jointly Understand Visual and Tactile Signals
Yichen Li, Yilun Du, Chao Liu et al.
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Nicholas Polizzi et al.
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
XU HAN, Caihua Shan, Yifei Shen et al.
Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs
Lean Wang, Wenkai Yang, Deli Chen et al.
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
Yazheng Yang, Yuqi Wang, Guang Liu et al.
Jointly-Learned Exit and Inference for a Dynamic Neural Network
Florence Regol, Joud Chataoui, Mark Coates
Private Zeroth-Order Nonsmooth Nonconvex Optimization
Qinzi Zhang, Hoang Tran, Ashok Cutkosky
Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Gourav Datta, Zeyu Liu, Peter Beerel
Scalable Language Model with Generalized Continual Learning
Bohao PENG, Zhuotao Tian, Shu Liu et al.
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
Haozhao Wang, Haoran Xu, Yichen Li et al.
WebArena: A Realistic Web Environment for Building Autonomous Agents
Shuyan Zhou, Frank F Xu, Hao Zhu et al.
Consistent Video-to-Video Transfer Using Synthetic Dataset
Jiaxin Cheng, Tianjun Xiao, Tong He
Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism
Tingting Jiang, Qi Xu, Xuming Ran et al.
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
Sheng Xu, Guiliang Liu
Influencer Backdoor Attack on Semantic Segmentation
Haoheng Lan, Jindong Gu, Philip Torr et al.
Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network
Tianze Luo, Zhanfeng Mo, Sinno Pan
The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models
cheng shi, Sibei Yang
LCOT: Linear Circular Optimal Transport
ROCIO DIAZ MARTIN, Ivan Medri, Yikun Bai et al.
REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
Maxwell Xu, Alexander Moreno, Hui Wei et al.
T-Rep: Representation Learning for Time Series using Time-Embeddings
Archibald Fraikin, Adrien Bennetot, Stephanie Allassonniere
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Shuhai Zhang, Yiliao Song, Jiahao Yang et al.
On Representation Complexity of Model-based and Model-free Reinforcement Learning
Hanlin Zhu, Baihe Huang, Stuart Russell
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model
Jiahao Li, Hao Tan, Kai Zhang et al.
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics
Suresh Suresh, Jayadeva Jayadeva, Sayan Ranu et al.
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following
Renze Lou, Kai Zhang, Jian Xie et al.
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
Bo Peng, Yadan Luo, Yonggang Zhang et al.
Convolutional Deep Kernel Machines
Edward Milsom, Ben Anson, Laurence Aitchison
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
Shaopeng Fu, Di Wang
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
Bo Zhang, Xinyu Cai, Jiakang Yuan et al.
I-PHYRE: Interactive Physical Reasoning
Shiqian Li, Kewen Wu, Chi Zhang et al.
Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips
Man Yao, Jiakui Hu, Tianxiang Hu et al.
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings
Edouard YVINEC, Arnaud Dapogny, Kevin Bailly
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Haoning Wu, Zicheng Zhang, Erli Zhang et al.
AutoLoRa: An Automated Robust Fine-Tuning Framework
Xilie Xu, Jingfeng Zhang, Mohan Kankanhalli
Dropout Enhanced Bilevel Training
Peiran Yu, Junyi Li, Heng Huang
Efficient Modulation for Vision Networks
Xu Ma, Xiyang Dai, Jianwei Yang et al.
Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression
Yufeng Zhang, Hang Yu, Jianguo Li et al.
Discovering modular solutions that generalize compositionally
Simon Schug, Seijin Kobayashi, Yassir Akram et al.
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
Mingxiao Li, Tingyu Qu, Ruicong Yao et al.
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Linus Bleistein, Agathe Guilloux
Robust Angular Synchronization via Directed Graph Neural Networks
Yixuan He, Gesine Reinert, David Wipf et al.
Improving protein optimization with smoothed fitness landscapes
Andrew Kirjner, Jason Yim, Raman Samusevich et al.
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity
Andrew Luo, Maggie Henderson, Michael Tarr et al.
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
Shengjie Luo, Tianlang Chen, Aditi Krishnapriyan
Online Information Acquisition: Hiring Multiple Agents
Federico Cacciamani, Matteo Castiglioni, Nicola Gatti
TabR: Tabular Deep Learning Meets Nearest Neighbors
Yury Gorishniy, Ivan Rubachev, Nikolay Kartashev et al.
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
Amirhossein Vahidi, Simon Schosser, Lisa Wimmer et al.
Scaling physics-informed hard constraints with mixture-of-experts
Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation
Josh Alman, Zhao Song
A Discretization Framework for Robust Contextual Stochastic Optimization
Rares Cristian, Georgia Perakis
Chain of Log-Concave Markov Chains
Saeed Saremi, Ji Won Park, Francis Bach
Protein Discovery with Discrete Walk-Jump Sampling
Nathan Frey, Dan Berenberg, Karina Zadorozhny et al.
A Simple and Scalable Representation for Graph Generation
Yunhui Jang, Seul Lee, Sungsoo Ahn
TokenFlow: Consistent Diffusion Features for Consistent Video Editing
Michal Geyer, Omer Bar Tal, Shai Bagon et al.
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts
Ahmed Hendawy, Jan Peters, Carlo D'Eramo
HYPO: Hyperspherical Out-Of-Distribution Generalization
Haoyue Bai, Yifei Ming, Julian Katz-Samuels et al.
On the Foundations of Shortcut Learning
Katherine Hermann, Hossein Mobahi, Thomas FEL et al.
Emergent Communication with Conversational Repair
Mitja Nikolaus
HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance
Junzhe Zhu, Peiye Zhuang, Sanmi Koyejo
Why is SAM Robust to Label Noise?
Christina Baek, J Kolter, Aditi Raghunathan
An Efficient Tester-Learner for Halfspaces
Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos et al.
Batch normalization is sufficient for universal function approximation in CNNs
Rebekka Burkholz
ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
William Yang, Byron Zhang, Olga Russakovsky
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
Renbo Tu, Colin White, Jean Kossaifi et al.
Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
Haoran Deng, Yang Yang, Jiahe Li et al.
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
Biswadeep Chakraborty, Beomseok Kang, Harshit Kumar et al.
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
Ilyass Hammouamri, Ismail Khalfaoui Hassani, Timothée Masquelier
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri et al.
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
Linlu Qiu, Liwei Jiang, Ximing Lu et al.
Scaling Laws for Sparsely-Connected Foundation Models
Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby et al.
A Policy Gradient Method for Confounded POMDPs
Mao Hong, Zhengling Qi, Yanxun Xu
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
Yinya Huang, Xiaohan Lin, Zhengying Liu et al.
On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs
Jen-tse Huang, Wenxuan Wang, Eric John Li et al.
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
Seungcheol Park, Hojun Choi, U Kang
Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape
Rundi Wu, Ruoshi Liu, Carl Vondrick et al.
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric
Daniel Severo, Lucas Theis, Johannes Ballé
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya et al.
GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
Haitao Yang, Xiangru Huang, Bo Sun et al.
MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations
Hanlei Zhang, Xin Wang, Hua Xu et al.
Localizing and Editing Knowledge In Text-to-Image Generative Models
Samyadeep Basu, Nanxuan Zhao, Vlad Morariu et al.
Linear attention is (maybe) all you need (to understand Transformer optimization)
Kwangjun Ahn, Xiang Cheng, Minhak Song et al.
Simplicial Representation Learning with Neural $k$-Forms
Kelly Maggs, Celia Hacker, Bastian Rieck
Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data
Ce Ju, Reinmar Kobler, Liyao Tang et al.
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
Zishun Yu, Yunzhe Tao, Liyu Chen et al.
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
Bohang Zhang, Jingchu Gai, Yiheng Du et al.
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He, Han Zhong, Zhuoran Yang