Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li
ICLR 2024 | May 2024
2024年5月7日 –
2024年5月11日
Microsoft at ICLR 2024
Central European Time (UTC +1)
地点： Vienna, Austria
论文与出版物
按年份分类的论文与出版物
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang (Eric) Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Ahmed Awadallah, Ryen W. White, Doug Burger, Chi Wang
COLM 2024 | August 2024
Best Paper, LLM Agents Workshop ICLR'24
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
CNN Kernels Can Be the Best Shapelets
Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li
The Twelfth International Conference on Learning Representations | May 2024
Coco-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha Dutell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz
ICLR 2024 | April 2024
Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, Ashton Anderson
ICLR 2024 | May 2024
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma (manik)
ICLR 2024 | April 2024
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Qiang Lou, Jian Jiao, Denis Charles
ICLR 2024 | May 2024
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, E. Chang, Hanwang Zhang
ICLR 2024 | January 2024
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
ICLR 2024 | March 2024
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Harnessing Density Ratios for Online Reinforcement Learning
P. Amortila, Dylan Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
ICLR 2024 | January 2024
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
ICLR 2024 | February 2024
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
ICLR 2024 | January 2024
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
Kosmos-G: Generating Images in Context with Multimodal Large Language Models
Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, Furu Wei
ICLR 2024 | May 2024
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
Mixture of LoRA Experts
ICLR 2024 | April 2024
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
ICLR 2024 (Oral) | May 2024
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024 International Conference on Learning Representations | January 2024
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman
ICLR 2024 | January 2024
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024 International Conference on Learning Representations | May 2024
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
ICLR 2024 | April 2024
Unifying Feature and Cost Aggregation with Transformers for Dense Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
International Conference on Learning Representations (ICLR) | May 2024
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity
Saeed Amizadeh, Kazuhito Koishida
2024 International Conference on Learning Representations | May 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | May 2024
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | March 2024
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3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yu-Qi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, Qi-Xing Huang
ICLR 2024 | April 2023
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Haoran Xu, Young Jin Kim, Amr Sharaf, Hany Hassan Awadalla
Accepted to ICLR 2024 | September 2023
Adapting Large Language Models via Reading Comprehension
Daixuan Cheng, Shaohan Huang, Furu Wei
ICLR 2024 | September 2023
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
ICLR 2024 | December 2023
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
September 2023
Augmenting transformers with recursively composed multi-grained representations
Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu
ICLR 2024 | September 2023
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham
ICLR 2024 | August 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
Better Neural PDE Solvers Through Data-Free Mesh Movers
Peiyan Hu, Yue Wang, Zhi-Ming Ma
ICLR 2024 | December 2023
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
Adam Block, Dylan Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
ICLR 2024 | October 2023
Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
ICLR 2024 | May 2023
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
ICLR 2024 | May 2023
Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning
Shitong Duan, Xiaoyuan Yi, Peng Zhang, T. Lu, Xing Xie, Ning Gu
ICLR 2024 | October 2023
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, A. Odisho, Bin Yu
ICLR 2024 | May 2023
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R. Glass, Pengcheng He
ICLR 2024 | September 2023
DyVal: Graph-informed Dynamic Evaluation of Large Language Models
Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie
ICLR 2024 | September 2023
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu
ICLR 2024 | October 2023
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
Peiyan Zhang, Hao Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang
ICLR 2024 | August 2023
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
M. Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia
ICLR 2024 | October 2023
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Aldo Pacchiano, A. Kolobov, Ching-An Cheng
ICLR 2024 | May 2023
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Jing Hu, Haixun Wang, Si-Qing Chen, Furu Wei
ICLR 2024 | July 2023
In-Context Learning through the Bayesian Prism
Kabir Ahuja, Madhur Panwar, Navin Goyal
ICLR 2024 | June 2023
Is Self-Repair a Silver Bullet for Code Generation?
Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama
ICLR 2024 | June 2023
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Peshawaria, Ranjita Naik, Besmira Nushi
October 2023
Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei, Minlie Huang
ICLR 2024 | June 2023
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
ICLR 2024 | October 2023
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling
ICLR 2024 | September 2023
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan
ICLR 2024 | September 2023
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
ICLR 2024 | October 2023
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
April 2023
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chun-yue Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
ICLR 2024 | October 2023
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Y. Yacoob, Lijuan Wang
ICLR 2024 | June 2023
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi Jaakkola, Jake Smith
ICLR 2024 | October 2023
MRVM-NeRF: Mask-Based Pretraining for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu
ICLR 2024 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt
ICLR 2024 | September 2023
Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shi-Bo Zhang, Yue Zhang
ICLR 2024 | June 2023
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li
ICLR 2024 | October 2023
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
ICLR 2024 | October 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation
Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang
ICLR 2024 | July 2023
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang
ICLR 2024 | September 2023
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
ICLR 2024 | September 2023
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
ICLR 2024 | October 2023
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He
ICLR 2024 | October 2023
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Y. Ma, Huan Yang, Wenhan Yang, Jianlong Fu, Jiaying Liu
ArXiv | May 2023, 第 abs/2305.15357 卷
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Weirong Ye, Xing Xie, Weizhu Chen, Yue Zhang
ICLR 2024 | December 2023
Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Simoes Ribeiro, Varun Chandrasekaran, Subhabrata (Subho) Mukherjee, Arindam Mitra, Ahmed Awadallah, Ece Kamar
ICLR 2024 | October 2023
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
ICLR 2024 | November 2023
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian R. Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
ICLR 2024 | October 2023
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Sai Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, H. Shum, Jian Guo
ICLR 2024 | July 2023
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
ICLR 2024 | September 2023
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
ICLR 2024 | September 2023
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon
ICLR 2024 | September 2023
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo
ICLR 2024 | August 2023
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin 林庆维, Daxin Jiang (姜大昕)
ICLR 2024 | June 2023
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Daxin Jiang (姜大昕)
ICLR 2024 | April 2023
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How to Fine-Tune Vision Models with SGD
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICLR 2024 | November 2022
按研究领域分类的论文与出版物
-
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma (manik)
ICLR 2024 | April 2024
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
ICLR 2024 | March 2024
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
April 2023
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
-
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yu-Qi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, Qi-Xing Huang
ICLR 2024 | April 2023
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Haoran Xu, Young Jin Kim, Amr Sharaf, Hany Hassan Awadalla
Accepted to ICLR 2024 | September 2023
Adapting Large Language Models via Reading Comprehension
Daixuan Cheng, Shaohan Huang, Furu Wei
ICLR 2024 | September 2023
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
ICLR 2024 | December 2023
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li
ICLR 2024 | May 2024
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
September 2023
Augmenting transformers with recursively composed multi-grained representations
Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu
ICLR 2024 | September 2023
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang (Eric) Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Ahmed Awadallah, Ryen W. White, Doug Burger, Chi Wang
COLM 2024 | August 2024
Best Paper, LLM Agents Workshop ICLR'24
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham
ICLR 2024 | August 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
Better Neural PDE Solvers Through Data-Free Mesh Movers
Peiyan Hu, Yue Wang, Zhi-Ming Ma
ICLR 2024 | December 2023
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
Adam Block, Dylan Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
ICLR 2024 | October 2023
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
CNN Kernels Can Be the Best Shapelets
Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li
The Twelfth International Conference on Learning Representations | May 2024
Coco-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha Dutell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz
ICLR 2024 | April 2024
Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
ICLR 2024 | May 2023
Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
ICLR 2024 | May 2023
Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning
Shitong Duan, Xiaoyuan Yi, Peng Zhang, T. Lu, Xing Xie, Ning Gu
ICLR 2024 | October 2023
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, Ashton Anderson
ICLR 2024 | May 2024
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, A. Odisho, Bin Yu
ICLR 2024 | May 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R. Glass, Pengcheng He
ICLR 2024 | September 2023
DyVal: Graph-informed Dynamic Evaluation of Large Language Models
Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie
ICLR 2024 | September 2023
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma (manik)
ICLR 2024 | April 2024
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Qiang Lou, Jian Jiao, Denis Charles
ICLR 2024 | May 2024
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, E. Chang, Hanwang Zhang
ICLR 2024 | January 2024
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu
ICLR 2024 | October 2023
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
ICLR 2024 | March 2024
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
Peiyan Zhang, Hao Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang
ICLR 2024 | August 2023
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
M. Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia
ICLR 2024 | October 2023
Harnessing Density Ratios for Online Reinforcement Learning
P. Amortila, Dylan Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
ICLR 2024 | January 2024
How to Fine-Tune Vision Models with SGD
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICLR 2024 | November 2022
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
ICLR 2024 | February 2024
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Aldo Pacchiano, A. Kolobov, Ching-An Cheng
ICLR 2024 | May 2023
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Jing Hu, Haixun Wang, Si-Qing Chen, Furu Wei
ICLR 2024 | July 2023
In-Context Learning through the Bayesian Prism
Kabir Ahuja, Madhur Panwar, Navin Goyal
ICLR 2024 | June 2023
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
ICLR 2024 | January 2024
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
Is Self-Repair a Silver Bullet for Code Generation?
Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama
ICLR 2024 | June 2023
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Peshawaria, Ranjita Naik, Besmira Nushi
October 2023
Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei, Minlie Huang
ICLR 2024 | June 2023
Kosmos-G: Generating Images in Context with Multimodal Large Language Models
Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, Furu Wei
ICLR 2024 | May 2024
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
ICLR 2024 | October 2023
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling
ICLR 2024 | September 2023
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan
ICLR 2024 | September 2023
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
ICLR 2024 | October 2023
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
April 2023
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chun-yue Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
ICLR 2024 | October 2023
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Y. Yacoob, Lijuan Wang
ICLR 2024 | June 2023
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
ICLR 2024 (Oral) | May 2024
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi Jaakkola, Jake Smith
ICLR 2024 | October 2023
MRVM-NeRF: Mask-Based Pretraining for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu
ICLR 2024 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt
ICLR 2024 | September 2023
Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shi-Bo Zhang, Yue Zhang
ICLR 2024 | June 2023
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
ICLR 2024 | October 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation
Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang
ICLR 2024 | July 2023
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024 International Conference on Learning Representations | January 2024
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang
ICLR 2024 | September 2023
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
ICLR 2024 | September 2023
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
ICLR 2024 | October 2023
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He
ICLR 2024 | October 2023
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman
ICLR 2024 | January 2024
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Y. Ma, Huan Yang, Wenhan Yang, Jianlong Fu, Jiaying Liu
ArXiv | May 2023, 第 abs/2305.15357 卷
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024 International Conference on Learning Representations | May 2024
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Weirong Ye, Xing Xie, Weizhu Chen, Yue Zhang
ICLR 2024 | December 2023
Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Simoes Ribeiro, Varun Chandrasekaran, Subhabrata (Subho) Mukherjee, Arindam Mitra, Ahmed Awadallah, Ece Kamar
ICLR 2024 | October 2023
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
ICLR 2024 | November 2023
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian R. Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
ICLR 2024 | October 2023
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Sai Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, H. Shum, Jian Guo
ICLR 2024 | July 2023
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
ICLR 2024 | September 2023
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
ICLR 2024 | April 2024
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
ICLR 2024 | September 2023
Unifying Feature and Cost Aggregation with Transformers for Dense Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
International Conference on Learning Representations (ICLR) | May 2024
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon
ICLR 2024 | September 2023
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo
ICLR 2024 | August 2023
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity
Saeed Amizadeh, Kazuhito Koishida
2024 International Conference on Learning Representations | May 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin 林庆维, Daxin Jiang (姜大昕)
ICLR 2024 | June 2023
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Daxin Jiang (姜大昕)
ICLR 2024 | April 2023
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | May 2024
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | March 2024
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FeatUp: A Model-Agnostic Framework for Features at Any Resolution
ICLR 2024 | March 2024
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
ICLR 2024 | January 2024
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024 International Conference on Learning Representations | May 2024
Unifying Feature and Cost Aggregation with Transformers for Dense Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
International Conference on Learning Representations (ICLR) | May 2024
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Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Qiang Lou, Jian Jiao, Denis Charles
ICLR 2024 | May 2024
Mixture of LoRA Experts
ICLR 2024 | April 2024
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li
ICLR 2024 | October 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman
ICLR 2024 | January 2024
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon
ICLR 2024 | September 2023
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AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang (Eric) Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Ahmed Awadallah, Ryen W. White, Doug Burger, Chi Wang
COLM 2024 | August 2024
Best Paper, LLM Agents Workshop ICLR'24
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
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Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, A. Odisho, Bin Yu
ICLR 2024 | May 2023
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
April 2023
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KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Peshawaria, Ranjita Naik, Besmira Nushi
October 2023
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
按类型分类的论文与出版物
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Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu
April 2023
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Y. Ma, Huan Yang, Wenhan Yang, Jianlong Fu, Jiaying Liu
ArXiv | May 2023, 第 abs/2305.15357 卷
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3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yu-Qi Yang, Yu-Xiao Guo, Hao Pan, Peng-Shuai Wang, Xin Tong, Yang Liu, Qi-Xing Huang
ICLR 2024 | April 2023
A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
Haoran Xu, Young Jin Kim, Amr Sharaf, Hany Hassan Awadalla
Accepted to ICLR 2024 | September 2023
Adapting Large Language Models via Reading Comprehension
Daixuan Cheng, Shaohan Huang, Furu Wei
ICLR 2024 | September 2023
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
ICLR 2024 | December 2023
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li
ICLR 2024 | May 2024
Augmenting transformers with recursively composed multi-grained representations
Xiang Hu, Qingyang Zhu, Kewei Tu, Wei Wu
ICLR 2024 | September 2023
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang (Eric) Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Ahmed Awadallah, Ryen W. White, Doug Burger, Chi Wang
COLM 2024 | August 2024
Best Paper, LLM Agents Workshop ICLR'24
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du, Robin Abraham
ICLR 2024 | August 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
Better Neural PDE Solvers Through Data-Free Mesh Movers
Peiyan Hu, Yue Wang, Zhi-Ming Ma
ICLR 2024 | December 2023
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
Adam Block, Dylan Foster, Akshay Krishnamurthy, Max Simchowitz, Cyril Zhang
ICLR 2024 | October 2023
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
CNN Kernels Can Be the Best Shapelets
Eric Qu, Yansen Wang, Xufang Luo, Wenqiang He, Kan Ren, Dongsheng Li
The Twelfth International Conference on Learning Representations | May 2024
Coco-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha Dutell, Mark Hamilton, Ayush Tewari, Simon Stent, William T. Freeman, Ruth Rosenholtz
ICLR 2024 | April 2024
Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
ICLR 2024 | May 2023
Combinatorial Bandits for Maximum Value Reward Function under Value-index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Proceedings of the 12th International Conference on Learning Representations (ICLR) | May 2024
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, Weizhu Chen
ICLR 2024 | May 2023
Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning
Shitong Duan, Xiaoyuan Yi, Peng Zhang, T. Lu, Xing Xie, Ning Gu
ICLR 2024 | October 2023
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, Ashton Anderson
ICLR 2024 | May 2024
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, A. Odisho, Bin Yu
ICLR 2024 | May 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo, Yoon Kim, James R. Glass, Pengcheng He
ICLR 2024 | September 2023
DyVal: Graph-informed Dynamic Evaluation of Large Language Models
Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie
ICLR 2024 | September 2023
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
Anirudh Buvanesh, Rahul Chand, Jatin Prakash, Bhawna Paliwal, Mudit Dhawan, Neelabh Madan, Deepesh Hada, Vidit Jain, Sonu Mehta, Yashoteja Prabhu, Manish Gupta, Ramachandran Ramjee, Manik Varma (manik)
ICLR 2024 | April 2024
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Qiang Lou, Jian Jiao, Denis Charles
ICLR 2024 | May 2024
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, E. Chang, Hanwang Zhang
ICLR 2024 | January 2024
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Y. Gat, Nitay Calderon, Amir Feder, Alexander Chapanin, Amit Sharma, Roi Reichart
ICLR 2024 | September 2023
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng, Jingbo Shang, Jianfeng Gao, Xiaodong Liu
ICLR 2024 | October 2023
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
ICLR 2024 | March 2024
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
Peiyan Zhang, Hao Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang
ICLR 2024 | August 2023
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
M. Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia
ICLR 2024 | October 2023
Harnessing Density Ratios for Online Reinforcement Learning
P. Amortila, Dylan Foster, Nan Jiang, Ayush Sekhari, Tengyang Xie
ICLR 2024 | January 2024
How to Fine-Tune Vision Models with SGD
Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar
ICLR 2024 | November 2022
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Ruehle, Laks V. S. Lakshmanan, Ahmed Awadallah
ICLR 2024 | February 2024
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Aldo Pacchiano, A. Kolobov, Ching-An Cheng
ICLR 2024 | May 2023
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Jing Hu, Haixun Wang, Si-Qing Chen, Furu Wei
ICLR 2024 | July 2023
In-Context Learning through the Bayesian Prism
Kabir Ahuja, Madhur Panwar, Navin Goyal
ICLR 2024 | June 2023
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo, Wenbin Li, Yuxin Li, Yang Gao
ICLR 2024 | January 2024
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
ICLR 2024 | January 2024
Spotlight
Is Self-Repair a Silver Bullet for Code Generation?
Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama
ICLR 2024 | June 2023
Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei, Minlie Huang
ICLR 2024 | June 2023
Kosmos-G: Generating Images in Context with Multimodal Large Language Models
Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, Furu Wei
ICLR 2024 | May 2024
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
ICLR 2024 | October 2023
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling
ICLR 2024 | September 2023
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Zecheng Tang, Chenfei Wu, Juntao Li, Nan Duan
ICLR 2024 | September 2023
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
ICLR 2024 | October 2023
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chun-yue Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
ICLR 2024 | October 2023
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Fuxiao Liu, Kevin Lin, Linjie Li, Jianfeng Wang, Y. Yacoob, Lijuan Wang
ICLR 2024 | June 2023
Mixture of LoRA Experts
ICLR 2024 | April 2024
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao
ICLR 2024 (Oral) | May 2024
MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design
Xiang Fu, Tian Xie, Andrew S. Rosen, Tommi Jaakkola, Jake Smith
ICLR 2024 | October 2023
MRVM-NeRF: Mask-Based Pretraining for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang, Yan Lu, Dong Liu
ICLR 2024 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
Tuan Le, Julian Cremer, Frank Noé, Djork-Arné Clevert, Kristof Schütt
ICLR 2024 | September 2023
Neural Structure Learning with Stochastic Differential Equations
Benjie Wang, Joel Jennings, Wenbo Gong
ICLR 2024 | November 2023
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Yidong Wang, Zhuohao Yu, Zhengran Zeng, Linyi Yang, Cunxiang Wang, Hao Chen, Chaoya Jiang, Rui Xie, Jindong Wang, Xing Xie, Wei Ye, Shi-Bo Zhang, Yue Zhang
ICLR 2024 | June 2023
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li
ICLR 2024 | October 2023
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu
ICLR 2024 | October 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation
Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu, Longbo Huang
ICLR 2024 | July 2023
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
Hangting Ye, Wei Fan, Xiaozhuang Song, Shun Zheng, He Zhao, Dandan Guo, Yi Chang
2024 International Conference on Learning Representations | January 2024
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, Hongyang Zhang
ICLR 2024 | September 2023
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
ICLR 2024 | September 2023
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Jose Miguel Hernandez-Lobato, Marwin Segler
ICLR 2024 | October 2023
Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective
Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, Pengcheng He
ICLR 2024 | October 2023
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman
ICLR 2024 | January 2024
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu, Liyue Shen
2024 International Conference on Learning Representations | May 2024
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao, Yidong Wang, Jindong Wang, Ruochen Xu, Weirong Ye, Xing Xie, Weizhu Chen, Yue Zhang
ICLR 2024 | December 2023
Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Simoes Ribeiro, Varun Chandrasekaran, Subhabrata (Subho) Mukherjee, Arindam Mitra, Ahmed Awadallah, Ece Kamar
ICLR 2024 | October 2023
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
ICLR 2024 | November 2023
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian R. Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
ICLR 2024 | October 2023
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Sai Wang, Chen Lin, Yeyun Gong, Lionel M. Ni, H. Shum, Jian Guo
ICLR 2024 | July 2023
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Minlie Huang, Nan Duan, Weizhu Chen
ICLR 2024 | September 2023
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang, Xiang Li, Dongsheng Li
ICLR 2024 | April 2024
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj
ICLR 2024 | September 2023
Unifying Feature and Cost Aggregation with Transformers for Dense Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim, Stephen Lin
International Conference on Learning Representations (ICLR) | May 2024
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon
ICLR 2024 | September 2023
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, Yuhui Yuan, Yutong Lin, Ze Liu, Chunyu Wang, Han Hu, Nanning Zheng, Baining Guo
ICLR 2024 | August 2023
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity
Saeed Amizadeh, Kazuhito Koishida
2024 International Conference on Learning Representations | May 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin 林庆维, Daxin Jiang (姜大昕)
ICLR 2024 | June 2023
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Daxin Jiang (姜大昕)
ICLR 2024 | April 2023
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | May 2024
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yang, Lei Yang, Yuxiong He
ICLR 2024 | March 2024
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Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, Besmira Nushi
September 2023
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Peshawaria, Ranjita Naik, Besmira Nushi
October 2023