ICLR 2024 Papers
2,297 papers found • Page 3 of 46
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification
Hang Yu, Cong Liao, Ruolan Liu et al.
Amortizing intractable inference in large language models
Edward Hu, Moksh Jain, Eric Elmoznino et al.
A Multi-Level Framework for Accelerating Training Transformer Models
Longwei Zou, Han Zhang, Yangdong Deng
A Mutual Information Perspective on Federated Contrastive Learning
Christos Louizos, Matthias Reisser, Denis Korzhenkov
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
Lijia Zhou, James Simon, Gal Vardi et al.
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden et al.
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks
Luong-Ha Nguyen, James-A. Goulet
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
Yiyang Zhou, Chenhang Cui, Jaehong Yoon et al.
Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps
Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi et al.
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
Sergei Solonets, Daniil Sinitsyn, Lukas Von Stumberg et al.
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Fei Kong, Jinhao Duan, ruipeng ma et al.
An Efficient Tester-Learner for Halfspaces
Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos et al.
An Emulator for Fine-tuning Large Language Models using Small Language Models
Eric Mitchell, Rafael Rafailov, Archit Sharma et al.
A Neural Framework for Generalized Causal Sensitivity Analysis
Dennis Frauen, Fergus Imrie, Alicia Curth et al.
A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines
Manju Garimella, Denizhan Pak, Justin Wood et al.
An Extensible Framework for Open Heterogeneous Collaborative Perception
Yifan Lu, Yue Hu, Yiqi Zhong et al.
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
Haochen Luo, Jindong Gu, Fengyuan Liu et al.
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei GUO, Ceyuan Yang, Anyi Rao et al.
An improved analysis of per-sample and per-update clipping in federated learning
Bo Li, Xiaowen Jiang, Mikkel N. Schmidt et al.
An interpretable error correction method for enhancing code-to-code translation
Min Xue, Artur Andrzejak, Marla Leuther
An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
Dongwon Son, Jaehyung Kim, Sanghyeon Son et al.
An Investigation of Representation and Allocation Harms in Contrastive Learning
Subha Maity, Mayank Agarwal, Mikhail Yurochkin et al.
An LLM can Fool Itself: A Prompt-Based Adversarial Attack
Xilie Xu, Keyi Kong, Ning Liu et al.
Annealing Self-Distillation Rectification Improves Adversarial Training
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
Qihang Zhou, Guansong Pang, Yu Tian et al.
An operator preconditioning perspective on training in physics-informed machine learning
Tim De Ryck, Florent Bonnet, Siddhartha Mishra et al.
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang et al.
An Unforgeable Publicly Verifiable Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu et al.
AnyText: Multilingual Visual Text Generation and Editing
Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He et al.
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Haoran Xu, Young Jin Kim, Amr Mohamed Nabil Aly Aly Sharaf et al.
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
A Plug-and-Play Image Registration Network
JUNHAO HU, Weijie Gan, Zhixin Sun et al.
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
A Policy Gradient Method for Confounded POMDPs
Mao Hong, Zhengling Qi, Yanxun Xu
Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams et al.
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
Ian Gemp, Luke Marris, Georgios Piliouras
A Precise Characterization of SGD Stability Using Loss Surface Geometry
Gregory Dexter, Borja Ocejo, Sathiya Keerthi et al.
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
Tatjana Chavdarova, Tong Yang, Matteo Pagliardini et al.
A Probabilistic Framework for Modular Continual Learning
Lazar Valkov, Akash Srivastava, Swarat Chaudhuri et al.
A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model
Zecheng Hao, Xinyu Shi, Zihan Huang et al.
A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora et al.
ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor
Tong Zhou, Shaolei Ren, Xiaolin Xu
A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
Izzeddin Gur, Hiroki Furuta, Austin Huang et al.
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
yisheng xiao, Juntao Li, Zechen Sun et al.
A Recipe for Improved Certifiable Robustness
Kai Hu, Klas Leino, Zifan Wang et al.
Are Human-generated Demonstrations Necessary for In-context Learning?
Rui Li, Guoyin Wang, Jiwei Li
Are Models Biased on Text without Gender-related Language?
Catarina Belém, Preethi Seshadri, Yasaman Razeghi et al.
A representation-learning game for classes of prediction tasks
Neria Uzan, Nir Weinberger
A Restoration Network as an Implicit Prior
Yuyang Hu, Mauricio Delbracio, Peyman Milanfar et al.