ICLR Papers
6,124 papers found • Page 79 of 123
A Foundation Model for Error Correction Codes
Yoni Choukroun, Lior Wolf
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller, Viktor Zaverkin, Johannes Kästner et al.
A Framework for Inference Inspired by Human Memory Mechanisms
Xiangyu Zeng, Jie Lin, Piao Hu et al.
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner, Frank Hutter, Luigi Nardi
A Generalist Agent
Jackie Kay, Sergio Gómez Colmenarejo, Mahyar Bordbar et al.
AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang et al.
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
Weize Chen, Yusheng Su, Jingwei Zuo et al.
AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation
Yuanwen Yue, Sabarinath Mahadevan, Jonas Schult et al.
A Good Learner can Teach Better: Teacher-Student Collaborative Knowledge Distillation
Ayan Sengupta, Shantanu Dixit, Md Shad Akhtar et al.
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Jintang Li, Huizhe Zhang, Ruofan Wu et al.
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
Zhengbo Wang, Jian Liang, Lijun Sheng et al.
A Hierarchical Bayesian Model for Few-Shot Meta Learning
Minyoung Kim, Timothy Hospedales
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang et al.
ALAM: Averaged Low-Precision Activation for Memory-Efficient Training of Transformer Models
Sunghyeon Woo, SunWoo Lee, Dongsuk Jeon
Algorithms for Caching and MTS with reduced number of predictions
Karim Ahmed Abdel Sadek, Marek Elias
Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic
Xiaoxiao Sun, Yue Yao, Shengjin Wang et al.
A Lie Group Approach to Riemannian Batch Normalization
Ziheng Chen, Yue Song, Yunmei Liu et al.
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Shiqiang Wang, Mingyue Ji
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye HAO et al.
Aligning Relational Learning with Lipschitz Fairness
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework
Eliya Segev, Maya Alroy, Ronen Katsir et al.
A Linear Algebraic Framework for Counterfactual Generation
Jong-Hoon Ahn, Akshay Vashist
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
Mingxiao Li, Tingyu Qu, Ruicong Yao et al.
AlpaGasus: Training a Better Alpaca with Fewer Data
Lichang Chen, Shiyang Li, Jun Yan et al.
Alt-Text with Context: Improving Accessibility for Images on Twitter
Nikita Srivatsan, Sofia Samaniego, Omar Florez et al.
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
Amortized Network Intervention to Steer the Excitatory Point Processes
Zitao Song, Wendi Ren, Shuang Li
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.