ICLR 2024

2,260 papers

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs

Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han

Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning

Ted Zadouri, Ahmet Üstün, Arash Ahmadian, Beyza Ermis, Acyr Locatelli

Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive

Yumeng Li, Margret Keuper, Dan Zhang, Anna Khoreva

Intelligent Switching for Reset-Free RL

Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn

Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness

Fran Jelenić, Josip Jukić, Martin Tutek, Mate Puljiz, Jan Šnajder

Course Correcting Koopman Representations

Mahan Fathi, Clement Gehring, Jonathan Pilault, David Kanaa, Pierre-Luc Bacon

Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks

David A. R. Robin, Kevin Scaman, marc lelarge

NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation

Pengfei Zheng, Yonggang Zhang, Zhen Fang, Tongliang Liu, Defu Lian

PB-LLM: Partially Binarized Large Language Models

Zhihang Yuan, Yuzhang Shang, Zhen Dong

Conformal Inductive Graph Neural Networks

Soroush H. Zargarbashi, Aleksandar Bojchevski

Does Writing with Language Models Reduce Content Diversity?

Vishakh Padmakumar, He He

Vision Transformers Need Registers

Timothée Darcet, Maxime Oquab, Julien Mairal, Piotr Bojanowski

Counterfactual Density Estimation using Kernel Stein Discrepancies

Diego Martinez-Taboada, Edward Kennedy

A Framework for Inference Inspired by Human Memory Mechanisms

Xiangyu Zeng, Jie Lin, Piao Hu, Ruizheng Huang, Zhicheng Zhang

One Forward is Enough for Neural Network Training via Likelihood Ratio Method

Jinyang Jiang, Zeliang Zhang, Chenliang Xu, Zhaofei Yu, Yijie Peng

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework

Maresa Schröder, Dennis Frauen, Stefan Feuerriegel

ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models

Sunghyeon Woo, Sunwoo Lee, Dongsuk Jeon

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

shrinivas ramasubramanian, Harsh Rangwani, Sho Takemori, Kunal Samanta, Yuhei Umeda

CAMBranch: Contrastive Learning with Augmented MILPs for Branching

Jiacheng Lin, Meng Xu, Zhihua Xiong, Huangang Wang

From Sparse to Soft Mixtures of Experts

Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa, Neil Houlsby

Learning 3D Particle-based Simulators from RGB-D Videos

William F Whitney, Tatiana Lopez-Guevara, Tobias Pfaff, Yulia Rubanova, Thomas Kipf

A 2-Dimensional State Space Layer for Spatial Inductive Bias

Ethan Baron, Itamar Zimerman, Lior Wolf

Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages

Jinyi Hu, Yuan Yao, Chongyi Wang, Shan Wang, Yinxu Pan

LOQA: Learning with Opponent Q-Learning Awareness

Milad Aghajohari, Juan Agustin Duque, Tim Cooijmans, Aaron Courville

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition

Chen Chen, Ruizhe Li, Yuchen Hu, Sabato Marco Siniscalchi, Pin-Yu Chen

Tree-Planner: Efficient Close-loop Task Planning with Large Language Models

Mengkang Hu, Yao Mu, Xinmiao Chelsey Yu, Mingyu Ding, Shiguang Wu

FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis

Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy Hospedales

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel

Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang

Discovering modular solutions that generalize compositionally

Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Maria Proca

Efficient and Scalable Graph Generation through Iterative Local Expansion

Andreas Bergmeister, Karolis Martinkus, Nathanael Perraudin, Roger Wattenhofer

SEPT: Towards Efficient Scene Representation Learning for Motion Prediction

Zhiqian Lan, Yuxuan Jiang, Yao Mu, Chen Chen, Shengbo Eben Li

An Investigation of Representation and Allocation Harms in Contrastive Learning

Subha Maity, Mayank Agarwal, Mikhail Yurochkin, Yuekai Sun

A path-norm toolkit for modern networks: consequences, promises and challenges

Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Remi Gribonval

Compressing LLMs: The Truth is Rarely Pure and Never Simple

Ajay Kumar Jaiswal, Zhe Gan, Xianzhi Du, Bowen Zhang, Zhangyang Wang

Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization

Anthony Bardou, Patrick Thiran, Thomas Begin

CODE REPRESENTATION LEARNING AT SCALE

Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati

Lemur: Harmonizing Natural Language and Code for Language Agents

Yiheng Xu, Hongjin Su, Chen Xing, Boyu Mi, Qian Liu

Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day

Yifan Jiang, Hao Tang, Jen-Hao Rick Chang, Liangchen Song, Zhangyang Wang

How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models

Pascal Chang, Jingwei Tang, Markus Gross, Vinicius C. Azevedo

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit

Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler, Aviv Tamar

A General Framework for User-Guided Bayesian Optimization

Carl Hvarfner, Frank Hutter, Luigi Nardi

Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition

Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin

Generalized Schrödinger Bridge Matching

Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos Theodorou

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs

Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti

Small-scale proxies for large-scale Transformer training instabilities

Mitchell Wortsman, Peter J Liu, Lechao Xiao, Katie E Everett, Alexander A Alemi

Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models

Zijun Wu, Yongkang Wu, Lili Mou

Oracle Efficient Algorithms for Groupwise Regret

Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani

Fast Value Tracking for Deep Reinforcement Learning

Frank Shih, Faming Liang

The Reasonableness Behind Unreasonable Translation Capability of Large Language Model

Tingchen Fu, Lemao Liu, Deng Cai, Guoping Huang, Shuming Shi

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks

Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia

A Restoration Network as an Implicit Prior

Yuyang Hu, Mauricio Delbracio, Peyman Milanfar, Ulugbek Kamilov

αTC-VAE: On the relationship between Disentanglement and Diversity

Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

Junyuan Hong, Jiachen T. Wang, Chenhui Zhang, Zhangheng Li, Bo Li

Model Merging by Uncertainty-Based Gradient Matching

Nico Daheim, Thomas Möllenhoff, Edoardo Ponti, Iryna Gurevych, Mohammad Emtiyaz Khan

Scalable Neural Network Kernels

Arijit Sehanobish, Krzysztof Marcin Choromanski, Yunfan Zhao, Kumar Avinava Dubey, Valerii Likhosherstov

SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet, Kilian Fatras, Jarrid Rector-Brooks

Matryoshka Diffusion Models

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly

LILO: Learning Interpretable Libraries by Compressing and Documenting Code

Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation

Mucong Ding, Bang An, Yuancheng Xu, Anirudh Satheesh, Furong Huang

Reward Design for Justifiable Sequential Decision-Making

Aleksa Sukovic, Goran Radanovic

Latent 3D Graph Diffusion

Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling

Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He

DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes

Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana V Davuluri

A Linear Algebraic Framework for Counterfactual Generation

Jong-Hoon Ahn, Akshay Vashist

Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach

Xinwei Zhang, Zhiqi Bu, Steven Wu, Mingyi Hong

Interpreting Robustness Proofs of Deep Neural Networks

Debangshu Banerjee, Avaljot Singh, Gagandeep Singh

MgNO: Efficient Parameterization of Linear Operators via Multigrid

Juncai He, Xinliang Liu, Jinchao Xu

Is Self-Repair a Silver Bullet for Code Generation?

Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama

Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs

Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L Leavitt, Naomi Saphra

Unified Generative Modeling of 3D Molecules with Bayesian Flow Networks

Yuxuan Song, Jingjing Gong, Hao Zhou, Mingyue Zheng, Jingjing Liu

BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection

Tinghao Xie, Xiangyu Qi, Ping He, Yiming Li, Jiachen T. Wang

SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos

Yulei Niu, Wenliang Guo, Long Chen, Xudong Lin, Shih-fu Chang

Improved Probabilistic Image-Text Representations

Sanghyuk Chun

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression

Runtian Zhai, Bingbin Liu, Andrej Risteski, J Zico Kolter, Pradeep Kumar Ravikumar

Test-Time Training on Nearest Neighbors for Large Language Models

Moritz Hardt, Yu Sun

Prediction Error-based Classification for Class-Incremental Learning

Michał Zając, Tinne Tuytelaars, Gido M van de Ven

Parametric Augmentation for Time Series Contrastive Learning

Xu Zheng, Tianchun Wang, Wei Cheng, Aitian Ma, Haifeng Chen

Polynomial Width is Sufficient for Set Representation with High-dimensional Features

Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li

GenSim: Generating Robotic Simulation Tasks via Large Language Models

Lirui Wang, Yiyang Ling, Zhecheng Yuan, Mohit Shridhar, Chen Bao

Representation Deficiency in Masked Language Modeling

Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records

Ethan Steinberg, Jason Alan Fries, Yizhe Xu, Nigam Shah

Conformal Language Modeling

Victor Quach, Adam Fisch, Tal Schuster, Adam Yala, Jae Ho Sohn

Critical Learning Periods Emerge Even in Deep Linear Networks

Michael Kleinman, Alessandro Achille, Stefano Soatto

Robust NAS under adversarial training: benchmark, theory, and beyond

Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios Chrysos, Volkan Cevher

Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning

Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan Ullman

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Yi-Lun Liao, Brandon M Wood, Abhishek Das, Tess Smidt

SOHES: Self-supervised Open-world Hierarchical Entity Segmentation

Shengcao Cao, Jiuxiang Gu, Jason Kuen, Hao Tan, Ruiyi Zhang

Look, Remember and Reason: Grounded Reasoning in Videos with Language Models

Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza, Mingu Lee, Pulkit Madan

Conditional Instrumental Variable Regression with Representation Learning for Causal Inference

Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu

Evaluating the Zero-shot Robustness of Instruction-tuned Language Models

Jiuding Sun, Chantal Shaib, Byron C Wallace

SmartPlay : A Benchmark for LLMs as Intelligent Agents

Yue Wu, XUAN TANG, Tom Mitchell, Yuanzhi Li

Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models

Ziyu Wang, Lejun Min, Gus Xia

Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations

Xiaolin Sun, Zizhan Zheng

Skill or Luck? Return Decomposition via Advantage Functions

Hsiao-Ru Pan, Bernhard Schölkopf

Learning dynamic representations of the functional connectome in neurobiological networks

Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley, Eviatar Yemini, Steven W. Zucker

Memory-Consistent Neural Networks for Imitation Learning

Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee

CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning

Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta

Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling

Jiarui Lu, Bozitao Zhong, Zuobai Zhang, Jian Tang