ICLR 2024

2,260 papers

In-Context Learning Learns Label Relationships but Is Not Conventional Learning

Jannik Kossen, Yarin Gal, Tom Rainforth

OpenChat: Advancing Open-source Language Models with Mixed-Quality Data

Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song

Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting

Yuxin Li, wenchao chen, Xinyue Hu, Bo Chen, Baolin Sun

R-MAE: Regions Meet Masked Autoencoders

Duy Kien Nguyen, Yanghao Li, Vaibhav Aggarwal, Martin R. Oswald, Alexander Kirillov

QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Yuhui Xu, Lingxi Xie, Xiaotao Gu, Xin Chen, Heng Chang

Image Inpainting via Tractable Steering of Diffusion Models

Anji Liu, Mathias Niepert, Guy Van den Broeck

Accelerated Sampling with Stacked Restricted Boltzmann Machines

Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco, Remi Monasson

STREAM: Spatio-TempoRal Evaluation and Analysis Metric for Video Generative Models

Pum Jun Kim, SeoJun Kim, Jaejun Yoo

Duolando: Follower GPT with Off-Policy Reinforcement Learning for Dance Accompaniment

Li Siyao, Tianpei Gu, Zhitao Yang, Zhengyu Lin, Ziwei Liu

Optimal transport based adversarial patch to leverage large scale attack transferability

Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin, Milad Leyli-abadi

Equivariant Matrix Function Neural Networks

Ilyes Batatia, Lars Leon Schaaf, Gabor Csanyi, Christoph Ortner, Felix Andreas Faber

LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection

Sifan Zhou, Liang Li, Xinyu Zhang, Bo Zhang, Shipeng Bai

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

Guangchi Fang, Qingyong Hu, Longguang Wang, Yulan Guo

Retro-fallback: retrosynthetic planning in an uncertain world

Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler, José Miguel Hernández-Lobato

State Representation Learning Using an Unbalanced Atlas

Li Meng, Morten Goodwin, Anis Yazidi, Paal E. Engelstad

MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field

Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang, Xuejin Chen, Zexiang Xu

Convergence of Bayesian Bilevel Optimization

Shi Fu, Fengxiang He, Xinmei Tian, Dacheng Tao

EControl: Fast Distributed Optimization with Compression and Error Control

Yuan Gao, Rustem Islamov, Sebastian U Stich

Learning Nash Equilibria in Rank-1 Games

Nikolas Patris, Ioannis Panageas

Learning invariant representations of time-homogeneous stochastic dynamical systems

Vladimir R Kostic, Pietro Novelli, Riccardo Grazzi, Karim Lounici, Massimiliano Pontil

BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation

Peng Xu, Wenqi Shao, Mengzhao Chen, Shitao Tang, Kaipeng Zhang

On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs

Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren

Fast and unified path gradient estimators for normalizing flows

Lorenz Vaitl, Ludwig Winkler, Lorenz Richter, Pan Kessel

Amortized Network Intervention to Steer the Excitatory Point Processes

Zitao Song, Wendi Ren, Shuang Li

ODEFormer: Symbolic Regression of Dynamical Systems with Transformers

Stéphane d'Ascoli, Sören Becker, Philippe Schwaller, Alexander Mathis, Niki Kilbertus

Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning

Antoine Bambade, Fabian Schramm, Adrien Taylor, Justin Carpentier

DiffEnc: Variational Diffusion with a Learned Encoder

Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi, Ole Winther

Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces

Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld

InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image

Jianhui Li, Shilong Liu, Zidong Liu, Yikai Wang, Kaiwen Zheng

Unveiling the Pitfalls of Knowledge Editing for Large Language Models

Zhoubo Li, Ningyu Zhang, Yunzhi Yao, Mengru Wang, Xi Chen

LCOT: Linear Circular Optimal Transport

Rocio P Diaz Martin, Ivan Vladimir Medri, Yikun Bai, Xinran Liu, Kangbai Yan

Bespoke Solvers for Generative Flow Models

Neta Shaul, Juan Pérez, Ricky T. Q. Chen, Ali Thabet, Albert Pumarola

Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval

Yongchao Du, Min Wang, Wengang Zhou, Shuping Hui, Houqiang Li

Decoding Natural Images from EEG for Object Recognition

Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang

Image Inpainting via Iteratively Decoupled Probabilistic Modeling

Wenbo Li, Xin Yu, Kun Zhou, Yibing Song, Zhe Lin

Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework

Eliya Segev, Maya Alroy, Ronen Katsir, Noam Wies, Ayana Shenhav

Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach

Xiang Lan, Hanshu Yan, Shenda Hong, Mengling Feng

Robust agents learn causal world models

Jonathan Richens, Tom Everitt

CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling

Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber

Fantastic Generalization Measures are Nowhere to be Found

Michael Gastpar, Ido Nachum, Jonathan Shafer, Thomas Weinberger

What's in a Prior? Learned Proximal Networks for Inverse Problems

Zhenghan Fang, Sam Buchanan, Jeremias Sulam

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach

Shaopeng Fu, Di Wang

Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing

Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu

CO2: Efficient Distributed Training with Full Communication-Computation Overlap

Weigao Sun, Zhen Qin, Weixuan Sun, Shidi Li, Dong Li

Towards Poisoning Fair Representations

Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li

Local Composite Saddle Point Optimization

Site Bai, Brian Bullins

Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts

Ahmed Hendawy, Jan Peters, Carlo D'Eramo

Neural Rate Control for Learned Video Compression

Yiwei Zhang, Guo Lu, Yunuo Chen, Shen Wang, Yibo Shi

Sliced Wasserstein Estimation with Control Variates

Khai Nguyen, nhật Hồ

Pre-Training and Fine-Tuning Generative Flow Networks

Ling Pan, Moksh Jain, Kanika Madan, Yoshua Bengio

Label-free Node Classification on Graphs with Large Language Models (LLMs)

Zhikai Chen, Haitao Mao, Hongzhi Wen, Haoyu Han, Wei Jin

Compositional Preference Models for Aligning LMs

Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Marc Dymetman

ARGS: Alignment as Reward-Guided Search

Maxim Khanov, Jirayu Burapacheep, Yixuan Li

Generative Sliced MMD Flows with Riesz Kernels

Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann

DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations

Zhihe Yang, Yunjian Xu

OWL: A Large Language Model for IT Operations

Hongcheng Guo, Jian Yang, Jiaheng Liu, Liqun Yang, Linzheng Chai

Efficient Streaming Language Models with Attention Sinks

Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis

Multi-task Learning with 3D-Aware Regularization

Wei-Hong Li, Steven McDonagh, Ales Leonardis, Hakan Bilen

Data Filtering Networks

Alex Fang, Albin Madappally Jose, Amit Jain, Ludwig Schmidt, Alexander T Toshev

A Branching Decoder for Set Generation

Zixian Huang, Gengyang Xiao, Yu Gu, Gong Cheng

V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection

Yichao Shen, Zigang Geng, YUHUI YUAN, Yutong Lin, Ze Liu

NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling

Kun Wang, Hao Wu, Yifan Duan, Guibin Zhang, Kai Wang

Scaling Laws of RoPE-based Extrapolation

Xiaoran Liu, Hang Yan, Chenxin An, Xipeng Qiu, Dahua Lin

Towards image compression with perfect realism at ultra-low bitrates

Marlene Careil, Matthew J. Muckley, Jakob Verbeek, Stéphane Lathuilière

Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings

Edouard YVINEC, Arnaud Dapogny, Kevin Bailly

Towards Understanding Sycophancy in Language Models

Mrinank Sharma, Meg Tong, Tomasz Korbak, David Duvenaud, Amanda Askell

SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Tim Dettmers, Ruslan A. Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar

Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset

Huigen Ye, Hua Xu, Hongyan Wang

Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning

Shuo He, Chaojie Wang, Guowu Yang, Lei Feng

RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations

Jiajun He, Gergely Flamich, Zongyu Guo, José Miguel Hernández-Lobato

Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning

Yucheng Yang, Tianyi Zhou, Qiang He, Lei Han, Mykola Pechenizkiy

Backdoor Federated Learning by Poisoning Backdoor-Critical Layers

Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li

Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs

Kaixuan Ji, Qingyue Zhao, Jiafan He, Weitong ZHANG, Quanquan Gu

Learning in reverse causal strategic environments with ramifications on two sided markets

Seamus Somerstep, Yuekai Sun, Yaacov Ritov

Learning Interactive Real-World Simulators

Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling

Stabilizing Backpropagation Through Time to Learn Complex Physics

Patrick Schnell, Nils Thuerey

Fast Imitation via Behavior Foundation Models

Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier

Repelling Random Walks

Isaac Reid, Eli Berger, Krzysztof Marcin Choromanski, Adrian Weller

HyperAttention: Long-context Attention in Near-Linear Time

Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David Woodruff

General Graph Random Features

Isaac Reid, Krzysztof Marcin Choromanski, Eli Berger, Adrian Weller

AlpaGasus: Training a Better Alpaca with Fewer Data

Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna

Intriguing Properties of Generative Classifiers

Priyank Jaini, Kevin Clark, Robert Geirhos

Democratizing Fine-grained Visual Recognition with Large Language Models

Mingxuan Liu, Subhankar Roy, Wenjing Li, Zhun Zhong, Nicu Sebe

Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems

Hyungjin Chung, Suhyeon Lee, Jong Chul Ye

Language Model Inversion

John Xavier Morris, Wenting Zhao, Justin T Chiu, Vitaly Shmatikov, Alexander M Rush

Perceptual Scales Predicted by Fisher Information Metrics

Jonathan Vacher, Pascal Mamassian

The LLM Surgeon

Tycho F. A. van der Ouderaa, Markus Nagel, Mart van Baalen, Tijmen Blankevoort

MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning

Yichuan Li, Xiyao Ma, Sixing Lu, Kyumin Lee, Xiaohu Liu

Self-Alignment with Instruction Backtranslation

Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy

Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.

Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines

A Recipe for Improved Certifiable Robustness

Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson

Masked Completion via Structured Diffusion with White-Box Transformers

Druv Pai, Sam Buchanan, Ziyang Wu, Yaodong Yu, Yi Ma

Let's Verify Step by Step

Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker

Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots

Xavier Puig, Eric Undersander, Andrew Szot, Mikael Dallaire Cote, Tsung-Yen Yang

Parameter-Efficient Multi-Task Model Fusion with Partial Linearization

Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu

Compressing Latent Space via Least Volume

Qiuyi Chen, Mark Fuge

On the Stability of Iterative Retraining of Generative Models on their own Data

Quentin Bertrand, Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel

Efficient local linearity regularization to overcome catastrophic overfitting

Elias Abad Rocamora, Fanghui Liu, Grigorios Chrysos, Pablo M. Olmos, Volkan Cevher

Neur2RO: Neural Two-Stage Robust Optimization

Justin Dumouchelle, Esther Julien, Jannis Kurtz, Elias Boutros Khalil

Mastering Memory Tasks with World Models

Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar