Klein, Dan

44 publications

ICLR 2026 GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning Lakshya A Agrawal, Shangyin Tan, Dilara Soylu, Noah Ziems, Rishi Khare, Krista Opsahl-Ong, Arnav Singhvi, Herumb Shandilya, Michael J Ryan, Meng Jiang, Christopher Potts, Koushik Sen, Alex Dimakis, Ion Stoica, Dan Klein, Matei Zaharia, Omar Khattab

ICLRW 2025 Diagnostic Uncertainty: Teaching Language Models to Describe Open-Ended Uncertainty Brian Sui, Jessy Lin, Michelle Li, Anca Dragan, Dan Klein, Jacob Steinhardt

CVPR 2025 Pose Priors from Language Models Sanjay Subramanian, Evonne Ng, Lea Müller, Dan Klein, Shiry Ginosar, Trevor Darrell

NeurIPS 2025 Why Do Multi-Agent LLM Systems Fail? Mert Cemri, Melissa Z Pan, Shuyi Yang, Lakshya A Agrawal, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya Parameswaran, Dan Klein, Kannan Ramchandran, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica

ICLRW 2025 Why Do Multiagent Systems Fail? Melissa Z Pan, Mert Cemri, Lakshya A Agrawal, Shuyi Yang, Bhavya Chopra, Rishabh Tiwari, Kurt Keutzer, Aditya Parameswaran, Kannan Ramchandran, Dan Klein, Joseph E. Gonzalez, Matei Zaharia, Ion Stoica

NeurIPSW 2024 Efficacy of Language Model Self-Play in Non-Zero-Sum Games Austen Liao, Nicholas Tomlin, Dan Klein

NeurIPS 2024 Explaining Datasets in Words: Statistical Models with Natural Language Parameters Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt

IJCAI 2024 Inferring Ontological Categories of OWL Classes Using Foundational Rules (Extended Abstract) Pedro Paulo F. Barcelos, Tiago Prince Sales, Elena Romanenko, João Paulo A. Almeida, Gal Engelberg, Dan Klein, Giancarlo Guizzardi

ICML 2024 Learning to Model the World with Language Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca Dragan

ICLR 2024 RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian

ICCV 2023 Can Language Models Learn to Listen? Evonne Ng, Sanjay Subramanian, Dan Klein, Angjoo Kanazawa, Trevor Darrell, Shiry Ginosar

ICLR 2023 Discovering Latent Knowledge in Language Models Without Supervision Collin Burns, Haotian Ye, Dan Klein, Jacob Steinhardt

NeurIPS 2023 Goal Driven Discovery of Distributional Differences via Language Descriptions Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt

ICML 2023 Poisoning Language Models During Instruction Tuning Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein

ICML 2022 Describing Differences Between Text Distributions with Natural Language Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

ICML 2021 Calibrate Before Use: Improving Few-Shot Performance of Language Models Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh

NeurIPS 2021 Learning Space Partitions for Path Planning Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E Gonzalez, Dan Klein, Yuandong Tian

ICLR 2020 Multilingual Alignment of Contextual Word Representations Steven Cao, Nikita Kitaev, Dan Klein

ICML 2020 Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez

NeurIPS 2018 Speaker-Follower Models for Vision-and-Language Navigation Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, Trevor Darrell

ICML 2017 Modular Multitask Reinforcement Learning with Policy Sketches Jacob Andreas, Dan Klein, Sergey Levine

CVPR 2016 Neural Module Networks Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein

NeurIPS 2015 On the Accuracy of Self-Normalized Log-Linear Models Jacob Andreas, Maxim Rabinovich, Michael I Jordan, Dan Klein

NeurIPS 2014 Unsupervised Transcription of Piano Music Taylor Berg-Kirkpatrick, Jacob Andreas, Dan Klein

AAAI 2011 Optimal Graph Search with Iterated Graph Cuts David Burkett, David Hall, Dan Klein

ICML 2010 Learning Programs: A Hierarchical Bayesian Approach Percy Liang, Michael I. Jordan, Dan Klein

ICML 2009 Learning from Measurements in Exponential Families Percy Liang, Michael I. Jordan, Dan Klein

NeurIPS 2009 Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs Alexandre Bouchard-côté, Slav Petrov, Dan Klein

NeurIPS 2008 Efficient Inference in Phylogenetic InDel Trees Alexandre Bouchard-côté, Dan Klein, Michael I. Jordan

ICML 2008 Fully Distributed EM for Very Large Datasets Jason Andrew Wolfe, Aria Haghighi, Dan Klein

ICML 2008 Structure Compilation: Trading Structure for Features Percy Liang, Hal Daumé Iii, Dan Klein

COLT 2008 Unsupervised Learning for Natural Language Processing Dan Klein

NeurIPS 2007 A Probabilistic Approach to Language Change Alexandre Bouchard-côté, Percy Liang, Dan Klein, Thomas L. Griffiths

AAAI 2007 A* Search via Approximate Factoring Aria Haghighi, John DeNero, Dan Klein

NeurIPS 2007 Agreement-Based Learning Percy Liang, Dan Klein, Michael I. Jordan

NeurIPS 2007 Discriminative Log-Linear Grammars with Latent Variables Slav Petrov, Dan Klein

AAAI 2007 Learning and Inference for Hierarchically Split PCFGs Slav Petrov, Dan Klein

UAI 2007 Mixture-of-Parents Maximum Entropy Markov Models David S. Rosenberg, Dan Klein, Ben Taskar

IJCAI 2003 Factored A* Search for Models over Sequences and Trees Dan Klein, Christopher D. Manning

IJCAI 2003 Spectral Learning Sepandar D. Kamvar, Dan Klein, Christopher D. Manning

NeurIPS 2002 Fast Exact Inference with a Factored Model for Natural Language Parsing Dan Klein, Christopher D. Manning

ICML 2002 From Instance-Level Constraints to Space-Level Constraints: Making the Most of Prior Knowledge in Data Clustering Dan Klein, Sepandar D. Kamvar, Christopher D. Manning

ICML 2002 Interpreting and Extending Classical Agglomerative Clustering Algorithms Using a Model-Based Approach Sepandar D. Kamvar, Dan Klein, Christopher D. Manning

NeurIPS 2001 Natural Language Grammar Induction Using a Constituent-Context Model Dan Klein, Christopher D. Manning