ICLR 2024

2,260 papers

PolyVoice: Language Models for Speech to Speech Translation

Qian qian Dong, Zhiying Huang, Qiao Tian, Chen Xu, Tom Ko

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science

Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu, Qi Liu

PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters

Jingyu Chen, Runlin Lei, Zhewei Wei

Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen

Scaling Convex Neural Networks with Burer-Monteiro Factorization

Arda Sahiner, Tolga Ergen, Batu Ozturkler, John M. Pauly, Morteza Mardani

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models

Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He

CoLiDE: Concomitant Linear DAG Estimation

Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper

REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning

Maxwell Xu, Alexander Moreno, Hui Wei, Benjamin Marlin, James Matthew Rehg

Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning

Yiwei Li, Peiwen Yuan, Shaoxiong Feng, Boyuan Pan, Xinglin Wang

Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning

Peizhong Ju, Arnob Ghosh, Ness Shroff

A Policy Gradient Method for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

HiGen: Hierarchical Graph Generative Networks

Mahdi Karami

MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data

Jiaxin Yin, Yuanyuan Qiao, Zitang Zhou, Xiangchao Wang, jie Yang

A Fast and Provable Algorithm for Sparse Phase Retrieval

Jian-Feng CAI, Yu Long, Ruixue WEN, Jiaxi Ying

Towards Transparent Time Series Forecasting

Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar

Out-Of-Domain Unlabeled Data Improves Generalization

seyed amir hossein saberi, Amir Najafi, Alireza Heidari, Mohammad Hosein Movasaghinia, Abolfazl Motahari

Effective Data Augmentation With Diffusion Models

Brandon Trabucco, Kyle Doherty, Max A Gurinas, Ruslan Salakhutdinov

Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment

Geyang Guo, Ranchi Zhao, Tianyi Tang, Xin Zhao, Ji-Rong Wen

Contrastive Difference Predictive Coding

Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits

Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li

Supervised Knowledge Makes Large Language Models Better In-context Learners

Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang

USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields

Moyang Li, Peng Wang, Lingzhe Zhao, Bangyan Liao, Peidong Liu

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning

Kostadin Garov, Dimitar Iliev Dimitrov, Nikola Jovanović, Martin Vechev

Score Models for Offline Goal-Conditioned Reinforcement Learning

Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks

Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, Henrik Boström

Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation

Ruoyu Wang, Yongqi Yang, Zhihao Qian, Ye Zhu, Yu Wu

Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs

Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun

CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models

Sreyan Ghosh, Ashish Seth, Sonal Kumar, Utkarsh Tyagi, Chandra Kiran Reddy Evuru

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning

Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum

A Precise Characterization of SGD Stability Using Loss Surface Geometry

Gregory Dexter, Borja Ocejo, Sathiya Keerthi, Aman Gupta, Ayan Acharya

Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback

Haolin Liu, Chen-Yu Wei, Julian Zimmert

ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models

Ilker Kesen, Andrea Pedrotti, Mustafa Dogan, Michele Cafagna, Emre Can Acikgoz

Lemur: Integrating Large Language Models in Automated Program Verification

Haoze Wu, Clark Barrett, Nina Narodytska

Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks

Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik, Jonathan Scholz

Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants

Peter Richtarik, Elnur Gasanov, Konstantin Pavlovich Burlachenko

Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency

Soumyadeep Pal, Yuguang Yao, REN WANG, Bingquan Shen, Sijia Liu

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI

Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida

Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning

Fan-Ming Luo, Tian Xu, Xingchen Cao, Yang Yu

Dynamic Layer Tying for Parameter-Efficient Transformers

Tamir David Hay, Lior Wolf

Consistent algorithms for multi-label classification with macro-at-k metrics

Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman

Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods

Yuto Nishimura, Taiji Suzuki

Tool-Augmented Reward Modeling

Lei Li, Yekun Chai, Shuohuan Wang, Yu Sun, Hao Tian

A Differentially Private Clustering Algorithm for Well-Clustered Graphs

Weiqiang He, Hendrik Fichtenberger, Pan Peng

Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace

Xinyu Yang, Weixin Liang, James Zou

PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation

Haopeng Sun, Lumin Xu, Sheng Jin, Ping Luo, Chen Qian

Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models

Seungcheol Park, Hojun Choi, U Kang

Scalable Monotonic Neural Networks

Hyunho Kim, Jong-Seok Lee

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks

Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha

How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir braverman, Quanquan Gu

MixSATGEN: Learning Graph Mixing for SAT Instance Generation

Xinyan Chen, Yang Li, Runzhong Wang, Junchi Yan

Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making

Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung

AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao

The Reversal Curse: LLMs trained on “A is B” fail to learn “B is A”

Lukas Berglund, Meg Tong, Maximilian Kaufmann, Mikita Balesni, Asa Cooper Stickland

Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings

Ilyass Hammouamri, Ismail Khalfaoui-Hassani, Timothée Masquelier

Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes

Ruiquan Huang, Yuan Cheng, Jing Yang, Vincent Tan, Yingbin Liang

Improving Offline RL by Blending Heuristics

Sinong Geng, Aldo Pacchiano, Andrey Kolobov, Ching-An Cheng

Explaining Kernel Clustering via Decision Trees

Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar

Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors

Ido Amos, Jonathan Berant, Ankit Gupta

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression

Lijia Zhou, James B Simon, Gal Vardi, Nathan Srebro

Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis

Hubert Siuzdak

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain

Yiming Gao, Feiyu Liu, Liang Wang, Dehua Zheng, Zhenjie Lian

What Makes a Good Prune? Maximal Unstructured Pruning for Maximal Cosine Similarity

Gabryel Mason-Williams, Fredrik Dahlqvist

Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting

Xinlu Zhang, Shiyang Li, Xianjun Yang, Chenxin Tian, Yao Qin

Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization

Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan, Ramesh Karri, Siddharth Garg

Neural Language of Thought Models

Yi-Fu Wu, Minseung Lee, Sungjin Ahn

Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems

Orren Karniol-Tambour, David M. Zoltowski, E. Mika Diamanti, Lucas Pinto, Carlos D Brody

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation

Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

Fiber Monte Carlo

Nick Richardson, Deniz Oktay, Yaniv Ovadia, James C Bowden, Ryan P Adams

Implicit Neural Representations and the Algebra of Complex Wavelets

T Mitchell Roddenberry, Vishwanath Saragadam, Maarten V. de Hoop, Richard Baraniuk

Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation

Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus

Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations

Patricia Pauli, Aaron J Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami

A Benchmark for Learning to Translate a New Language from One Grammar Book

Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi

How do Language Models Bind Entities in Context?

Jiahai Feng, Jacob Steinhardt

Active Retrosynthetic Planning Aware of Route Quality

Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang

Parsing neural dynamics with infinite recurrent switching linear dynamical systems

Victor Geadah, International Brain Laboratory, Jonathan W. Pillow

Efficient Subgraph GNNs by Learning Effective Selection Policies

Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

Distributionally Robust Optimization with Bias and Variance Reduction

Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui

Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts

Lizhang Chen, Bo Liu, Kaizhao Liang, Qiang Liu

Understanding Catastrophic Forgetting in Language Models via Implicit Inference

Suhas Kotha, Jacob Mitchell Springer, Aditi Raghunathan

3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining

Siming Yan, Yuqi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games

Brian Hu Zhang, Gabriele Farina, Tuomas Sandholm

Closing the Curious Case of Neural Text Degeneration

Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal

Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation

Prakhar Kaushik, Aayush Mishra, Adam Kortylewski, Alan Yuille

f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization

Sina Baharlouei, Shivam Patel, Meisam Razaviyayn

Eureka: Human-Level Reward Design via Coding Large Language Models

Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.

Ashutosh Singh, Ricardo Augusto Borsoi, Deniz Erdogmus, Tales Imbiriba

Estimating Shape Distances on Neural Representations with Limited Samples

Dean A Pospisil, Brett W. Larsen, Sarah E Harvey, Alex H Williams

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF

Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell

Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs

Aakash Lahoti, Stefani Karp, Ezra Winston, Aarti Singh, Yuanzhi Li

Improved algorithm and bounds for successive projection

Jiashun Jin, Tracy Ke, Gabriel Moryoussef, Jiajun Tang, Jingming Wang

Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference

Khalid Oublal, Said Ladjal, David Benhaiem, Emmanuel LE BORGNE, François Roueff

One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models

Sheng-jun Huang, Yi Li, Yiming Sun, Ying-Peng Tang

Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

Dipanjyoti Paul, Arpita Chowdhury, Xinqi Xiong, Feng-Ju Chang, David Edward Carlyn

Can LLM-Generated Misinformation Be Detected?

Canyu Chen, Kai Shu

Sharpness-Aware Minimization Enhances Feature Quality via Balanced Learning

Jacob Mitchell Springer, Vaishnavh Nagarajan, Aditi Raghunathan

AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ

Jonas Belouadi, Anne Lauscher, Steffen Eger

Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Community

Arman Isajanyan, Artur Shatveryan, David Kocharian, Zhangyang Wang, Humphrey Shi

PubDef: Defending Against Transfer Attacks From Public Models

Chawin Sitawarin, Jaewon Chang, David Huang, Wesson Altoyan, David Wagner