ICLR 2024

2,260 papers

Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping

Enming Liang, Minghua Chen

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit

Duanyi Yao, Songze Li, Ye XUE, Jin Liu

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning

Tianbao Xie, Siheng Zhao, Chen Henry Wu, Yitao Liu, Qian Luo

An Unforgeable Publicly Verifiable Watermark for Large Language Models

Aiwei Liu, Leyi Pan, Xuming Hu, Shuang Li, Lijie Wen

SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models

S. Fatemeh Seyyedsalehi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee

COSA: Concatenated Sample Pretrained Vision-Language Foundation Model

Sihan Chen, Xingjian He, Handong Li, Xiaojie Jin, Jiashi Feng

Win-Win: Training High-Resolution Vision Transformers from Two Windows

Vincent Leroy, Jerome Revaud, Thomas Lucas, Philippe Weinzaepfel

BRUSLEATTACK: A QUERY-EFFICIENT SCORE- BASED BLACK-BOX SPARSE ADVERSARIAL ATTACK

Quoc Viet Vo, Ehsan Abbasnejad, Damith Ranasinghe

AttEXplore: Attribution for Explanation with model parameters eXploration

Zhiyu Zhu, Huaming Chen, Jiayu Zhang, Xinyi Wang, Zhibo Jin

Effective pruning of web-scale datasets based on complexity of concept clusters

Amro Kamal Mohamed Abbas, Evgenia Rusak, Kushal Tirumala, Wieland Brendel, Kamalika Chaudhuri

Towards 3D Molecule-Text Interpretation in Language Models

Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He

Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World

Rujie Wu, Xiaojian Ma, Zhenliang Zhang, Wei Wang, Qing Li

The Need for Speed: Pruning Transformers with One Recipe

Samir Khaki, Konstantinos N Plataniotis

RLIF: Interactive Imitation Learning as Reinforcement Learning

Jianlan Luo, Perry Dong, Yuexiang Zhai, Yi Ma, Sergey Levine

An interpretable error correction method for enhancing code-to-code translation

Min Xue, Artur Andrzejak, Marla Leuther

Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation

Zhiyu Zhu, Xinyi Wang, Zhibo Jin, Jiayu Zhang, Huaming Chen

Scaling Laws for Associative Memories

Vivien Cabannes, Elvis DOHMATOB, Alberto Bietti

Fully Hyperbolic Convolutional Neural Networks for Computer Vision

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

Intriguing Properties of Data Attribution on Diffusion Models

Xiaosen Zheng, Tianyu Pang, Chao Du, Jing Jiang, Min Lin

MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations

Hanlei Zhang, Xin Wang, Hua Xu, Qianrui Zhou, Kai Gao

Diverse Projection Ensembles for Distributional Reinforcement Learning

Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan

Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video

Yanqin Jiang, Li Zhang, Jin Gao, Weiming Hu, Yao Yao

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss

Hao Wang, Chenyi Zhang, Tongyang Li

Noise-free Score Distillation

Oren Katzir, Or Patashnik, Daniel Cohen-or, Dani Lischinski

Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing

Minyang Hu, Hong Chang, Bingpeng MA, Shiguang Shan, Xilin Chen

ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation

Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk, Klaus Maier-Hein, Paul F Jaeger

Sparsistency for inverse optimal transport

Francisco Andrade, Gabriel Peyré, Clarice Poon

Neural Contractive Dynamical Systems

Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann

OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS

Lijia Yu, Xiao-Shan Gao, Lijun Zhang

Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks

Sina Khajehabdollahi, Roxana Zeraati, Emmanouil Giannakakis, Tim Jakob Schäfer, Georg Martius

The Generalization Gap in Offline Reinforcement Learning

Ishita Mediratta, Qingfei You, Minqi Jiang, Roberta Raileanu

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning

James Chapman, Lennie Wells, Ana Lawry Aguila

On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation

Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn

Robust Training of Federated Models with Extremely Label Deficiency

Yonggang Zhang, Zhiqin Yang, Xinmei Tian, Nannan Wang, Tongliang Liu

BadEdit: Backdooring Large Language Models by Model Editing

Yanzhou Li, Tianlin Li, Kangjie Chen, Jian Zhang, Shangqing Liu

Probabilistically Rewired Message-Passing Neural Networks

Chendi Qian, Andrei Manolache, Kareem Ahmed, Zhe Zeng, Guy Van den Broeck

Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs

Kejun Tang, Jiayu Zhai, Xiaoliang Wan, Chao Yang

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Guocheng Qian, Jinjie Mai, Abdullah Hamdi, Jian Ren, Aliaksandr Siarohin

Negative Label Guided OOD Detection with Pretrained Vision-Language Models

Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding

Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin

Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li

Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline

Donggyu Lee, Sangwon Jung, Taesup Moon

Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators

Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

On Harmonizing Implicit Subpopulations

Feng Hong, Jiangchao Yao, Yueming LYU, Zhihan Zhou, Ivor Tsang

Neural Fourier Transform: A General Approach to Equivariant Representation Learning

Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

The optimality of kernel classifiers in Sobolev space

Jianfa Lai, zhifan Li, Dongming Huang, Qian Lin

Towards Robust Out-of-Distribution Generalization Bounds via Sharpness

Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee

Training Unbiased Diffusion Models From Biased Dataset

Yeongmin Kim, Byeonghu Na, Minsang Park, JoonHo Jang, Dongjun Kim

Out-of-Variable Generalisation for Discriminative Models

Siyuan Guo, Jonas Bernhard Wildberger, Bernhard Schölkopf

Bandits with Replenishable Knapsacks: the Best of both Worlds

Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations

Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach

Learning Multi-Faceted Prototypical User Interests

Nhu-Thuat Tran, Hady W. Lauw

Online Information Acquisition: Hiring Multiple Agents

Federico Cacciamani, Matteo Castiglioni, Nicola Gatti

A Multi-Level Framework for Accelerating Training Transformer Models

Longwei Zou, Han Zhang, Yangdong Deng

AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation

Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult, Francis Engelmann, Bastian Leibe

Learning Optimal Contracts: How to Exploit Small Action Spaces

Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti

CPPO: Continual Learning for Reinforcement Learning with Human Feedback

Han Zhang, Yu Lei, Lin Gui, Min Yang, Yulan He

How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions

Lorenzo Pacchiardi, Alex James Chan, Sören Mindermann, Ilan Moscovitz, Alexa Yue Pan

Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning

Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, Shirui Pan

First-order ANIL provably learns representations despite overparametrisation

Oğuz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion

Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel

Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen

ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis

Luo donghao, wang xue

Human Feedback is not Gold Standard

Tom Hosking, Phil Blunsom, Max Bartolo

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo

Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup

DP-SGD Without Clipping: The Lipschitz Neural Network Way

Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet

Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging

Max Zimmer, Christoph Spiegel, Sebastian Pokutta

Improving Non-Transferable Representation Learning by Harnessing Content and Style

Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang

PeFLL: Personalized Federated Learning by Learning to Learn

Jonathan Scott, Hossein Zakerinia, Christoph H Lampert

DEEP NEURAL NETWORK INITIALIZATION WITH SPARSITY INDUCING ACTIVATIONS

Ilan Price, Nicholas Daultry Ball, Adam Christopher Jones, Samuel Chun Hei Lam, Jared Tanner

Retrieval-Enhanced Contrastive Vision-Text Models

Ahmet Iscen, Mathilde Caron, Alireza Fathi, Cordelia Schmid

C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee, Mark A. Hasegawa-Johnson, Yingzhen Li

Leveraging Uncertainty Estimates To Improve Classifier Performance

Gundeep Arora, Srujana Merugu, Anoop Saladi, Rajeev Rastogi

Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design

Jeff Guo, Philippe Schwaller

Reward-Free Curricula for Training Robust World Models

Marc Rigter, Minqi Jiang, Ingmar Posner

Light Schrödinger Bridge

Alexander Korotin, Nikita Gushchin, Evgeny Burnaev

Learning to Compose: Improving Object Centric Learning by Injecting Compositionality

Whie Jung, Jaehoon Yoo, Sungjin Ahn, Seunghoon Hong

ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update

Liyuan Mao, Haoran Xu, Weinan Zhang, Xianyuan Zhan

Magnushammer: A Transformer-Based Approach to Premise Selection

Maciej Mikuła, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang

Kalman Filter for Online Classification of Non-Stationary Data

Michalis Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh

SALMONN: Towards Generic Hearing Abilities for Large Language Models

Changli Tang, Wenyi Yu, Guangzhi Sun, Xianzhao Chen, Tian Tan

Cauchy-Schwarz Divergence Information Bottleneck for Regression

Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, Jose C Principe

Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation

Ryan Wong, Necati Cihan Camgoz, Richard Bowden

Toward effective protection against diffusion-based mimicry through score distillation

Haotian Xue, Chumeng Liang, Xiaoyu Wu, Yongxin Chen

Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model

Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang

Simplicial Representation Learning with Neural k-Forms

Kelly Maggs, Celia Hacker, Bastian Rieck

Prediction without Preclusion: Recourse Verification with Reachable Sets

Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun

Structural Inference with Dynamics Encoding and Partial Correlation Coefficients

Aoran Wang, Jun Pang

Revisiting Data Augmentation in Deep Reinforcement Learning

Jianshu Hu, Yunpeng Jiang, Paul Weng

Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics

Christian Gumbsch, Noor Sajid, Georg Martius, Martin V. Butz

Improving equilibrium propagation without weight symmetry through Jacobian homeostasis

Axel Laborieux, Friedemann Zenke

DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation

Hong Chen, Yipeng Zhang, Simin Wu, Xin Wang, Xuguang Duan

INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu

ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference

Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios Chrysos, Volkan Cevher

From Zero to Turbulence: Generative Modeling for 3D Flow Simulation

Marten Lienen, David Lüdke, Jan Hansen-Palmus, Stephan Günnemann

GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation

Guikun Xu, Yongquan Jiang, PengChuan Lei, yan yang, Jim Chen

Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks

Yanbo Wang, Jian Liang, Ran He

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data

Mihaela C Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia

Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram

Yeongyeon Na, Minje Park, Yunwon Tae, Sunghoon Joo