Preprints

  • How Well Does Agent Development Reflect Real-World Work?
    Zora Zhiruo Wang, Sanidhya Vijayvargiya, Aspen Chen, Hanmo Zhang, Venu Arvind Arangarajan, Jett Chen, Valerie Chen, Diyi Yang, Daniel Fried, Graham Neubig
    arXiv, 2026. site
  • Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
    Yiqing Xie, Emmy Liu, Gaokai Zhang, Nachiket Kotalwar, Shubham Gandhi, Sathwik Acharya, Xingyao Wang, Carolyn Rose, Graham Neubig, Daniel Fried
    arXiv, 2026. code
  • Position: Humans are Missing from AI Coding Agent Research
    Zora Zhiruo Wang*, John Yang*, Kilian Lieret*, Alexa Tartaglini, Valerie Chen, Yuxiang Wei, Zijian Wang, Lingming Zhang, Karthik Narasimhan, Ludwig Schmidt, Graham Neubig, Daniel Fried, Diyi Yang
    preprint, 2026.
  • Reasoning with Latent Tokens in Diffusion Language Models
    Andre He, Sean Welleck*, Daniel Fried*
    arXiv, 2026.
  • Propose, Solve, Verify: Self-Play Through Formal Verification
    Alex Wilf, Pranjal Aggarwal, Bryan Parno, Daniel Fried, Louis-Philippe Morency, Paul Pu Liang, Sean Welleck
    arXiv, 2025.
  • Toward Training Superintelligent Software Agents through Self-Play SWE-RL
    Yuxiang Wei, Zhiqing Sun, Emily McMilin, Jonas Gehring, David Zhang, Gabriel Synnaeve, Daniel Fried, Lingming Zhang, Sida Wang
    arXiv, 2025.
  • Measuring Fine-Grained Negotiation Tactics of Humans and LLMs in Diplomacy
    Wenkai Li*, Lynnette Hui Xian Ng*, Andy Liu, Daniel Fried
    arXiv, 2025.
  • How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations
    Zora Zhiruo Wang, Yijia Shao, Omar Shaikh, Daniel Fried, Graham Neubig, Diyi Yang
    arXiv, 2025.
  • Success and Cost Elicit Convention Formation for Efficient Communication
    Saujas Vaduguru, Yilun Hua, Yoav Artzi, Daniel Fried
    arXiv, 2025.
  • Analyzing Information Sharing and Coordination in Multi-Agent Planning
    Tianyue Ou, Saujas Vaduguru, Daniel Fried
    arXiv, 2025.
  • MetaLint: Generalizable Idiomatic Code Quality Analysis through Instruction-Following and Easy-to-Hard Generalization
    Atharva Naik, Lawanya Baghel, Dhakshin Govindarajan, Darsh Agrawal, Daniel Fried, Carolyn Rose
    arXiv, 2025.
  • CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
    Yiqing Xie, Alex Xie, Divyanshu Sheth, Pengfei Liu, Daniel Fried, and Carolyn Rose
    arXiv, 2024.

    • 2026

  • Generative Value Conflicts Reveal LLM Priorities
    Andy Liu, Kshitish Ghate, Mona Diab*, Daniel Fried*, Atoosa Kasirzadeh*, Max Kleiman-Weiner*
    ICLR, 2026. code
  • From Reproduction to Replication: Evaluating Research Agents with Progressive Code Masking
    Gyeongwon James Kim, Alex Wilf, Louis-Philippe Morency, Daniel Fried
    ICLR, 2026. code

    • 2025

  • SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
    Yuxiang Wei, Olivier Duchenne, Jade Copet, Quentin Carbonneaux, Lingming Zhang, Daniel Fried, Gabriel Synnaeve, Rishabh Singh, and Sida I. Wang
    NeurIPS, 2025. code
  • Identifying and Interactively Refining Ambiguous User Goals for Data Visualization Code Generation
    Mert Inan, Anthony Sicilia, Alex Xie, Saujas Vaduguru, Daniel Fried, and Malihe Alikhani
    EMNLP, 2025.
  • Rewarding the Unlikely: Lifting GRPO Beyond Distribution Sharpening
    Andre He, Daniel Fried, and Sean Welleck
    EMNLP, 2025.
  • mrCAD: Multimodal Refinement of Computer-aided Designs
    William P. McCarthy, Saujas Vaduguru, Karl D. D. Willis, Justin Matejka, Judith E. Fan, Daniel Fried, and Yewen Pu
    Findings of EMNLP, 2025. dataset
  • Inducing Programmatic Skills for Agentic Tasks
    Zora Zhiruo Wang, Apurva Gandhi, Graham Neubig, Daniel Fried
    COLM, 2025. code
  • RepoST: Scalable Repository-Level Coding Environment Construction with Sandbox Testing
    Yiqing Xie, Alex Xie, Divyanshu Sheth, Pengfei Liu, Daniel Fried, Carolyn Rose
    COLM, 2025. code
  • Improving Model Factuality with Fine-grained Critique-based Evaluator
    Yiqing Xie, Wenxuan Zhou, Pradyot Prakash, Di Jin, Yuning Mao, Quintin Fettes, Arya Talebzadeh, Sinong Wang, Han Fang, Carolyn Rose, Daniel Fried, and Hejia Zhang
    ACL, 2025.
  • Agent Workflow Memory
    Zora Zhiruo Wang, Jiayuan Mao, Daniel Fried, and Graham Neubig
    ICML, 2025. code
  • Dynamic Coalition Structure Detection in Natural Language-based Interactions
    Abhishek N. Kulkarni*, Andy Liu*, Jean-Raphael Gaglione, Daniel Fried, and Ufuk Topcu
    AAMAS, 2025.
  • AutoPresent: Designing Structured Visuals from Scratch
    Jiaxin Ge*, Zora Zhiruo Wang*, Xuhui Zhou, Yi-Hao Peng, Sanjay Subramanian, Qinyue Tan, Maarten Sap, Alane Suhr**, Daniel Fried**, Graham Neubig**, and Trevor Darrell**
    CVPR, 2025. code
  • CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells
    Atharva Naik, Marcus Alenius, Daniel Fried, and Carolyn Rose
    NAACL, 2025.
  • CodeRAG-Bench: Can Retrieval Augment Code Generation?
    Zora Zhiruo Wang*, Akari Asai*, Xinyan Velocity Yu, Frank F. Xu, Yiqing Xie, Graham Neubig, and Daniel Fried
    Findings of NAACL, 2025. project page, code
  • BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
    Terry Yue Zhuo et al. (33 authors from the BigCode project)
    ICLR, 2025. project page, code
  • Human-Aligned Chess with a Bit of Search
    Yiming Zhang, Athul Paul Jacob, Vivian Lai, Daniel Fried, and Daphne Ippolito
    ICLR, 2025. code and models
  • Repetition Improves Language Model Embeddings
    Jacob Mitchell Springer, Suhas Kotha, Daniel Fried, Graham Neubig, and Aditi Raghunathan
    ICLR, 2025.
  • Dissecting Adversarial Robustness of Multimodal LM Agents
    Chen Henry Wu, Rishi Shah, Jing Yu Koh, Ruslan Salakhutdinov, Daniel Fried, and Aditi Raghunathan
    ICLR, 2025. project page
  • Tree Search for Language Model Agents
    Jing Yu Koh, Stephen McAleer, Daniel Fried, and Ruslan Salakhutdinov
    TMLR, 2025. code, project page

    • 2024

  • Comparative Knowledge Distillation
    Alex Tianyi Xu*, Alex Wilf*, Paul Pu Liang, Alexander Obolenskiy, Daniel Fried, and Louis-Philippe Morency
    WACV, 2024.
  • ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
    Siddhant Waghjale*, Vishruth Veerendranath*, Zora Zhiruo Wang, and Daniel Fried
    EMNLP, 2024. code, project page
  • What Are Tools Anyway? A Survey from the Language Model Perspective
    Zora Zhiruo Wang, Zhoujun Cheng, Hao Zhu, Daniel Fried, and Graham Neubig
    COLM, 2024.
  • Human-Agent Cooperation in Games under Incomplete Information through Natual Language Communication
    Shenghui Chen, Daniel Fried, and Ufuk Topcu
    IJCAI, 2024.
  • Evaluating Large Language Model Biases in Person-Steered Generation
    Andy Liu, Mona T. Diab, and Daniel Fried
    Findings of ACL, 2024.
  • Is the Pope Catholic? Yes, the Pope is Catholic. Generative Evaluation of Intent Resolution in LLMs
    Akhila Yerukola, Saujas Vaduguru, Daniel Fried, and Maarten Sap
    ACL, 2024.
  • VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
    Jing Yu Koh, Robert Lo*, Lawrence Jang*, Vikram Duvvur*, Ming Chong Lim*, Po-Yu Huang*, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, and Daniel Fried
    ACL, 2024.
  • TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks
    Zhiruo Wang, Graham Neubig, and Daniel Fried
    ICML, 2024. code
  • Amortizing Pragmatic Program Synthesis with Rankings
    Yewen Pu, Saujas Vaduguru, Priyan Vaithilingam, Elena Glassman, and Daniel Fried
    ICML, 2024.
  • Asking More Informative Questions for Grounded Retrieval
    Sedrick Keh, Justin T. Chiu, and Daniel Fried
    Findings of NAACL, 2024.
  • Generating Pragmatic Examples to Train Neural Program Synthesizers
    Saujas Vaduguru, Daniel Fried, and Yewen Pu
    ICLR, 2024.
  • Sotopia: Interactive Evaluation for Social Intelligence in Language Agents
    Xuhui Zhou*, Hao Zhu*, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, and Maarten Sap
    ICLR, 2024. project page
  • WebArena: A Realistic Web Environment for Building Autonomous Agents
    Shuyan Zhou*, Frank Xu*, Hao Zhu**, Xuhui Zhou**, Robert Lo**, Abishek Sridhar**, Xianyi Cheng, Yonatan Bisk, Daniel Fried, Uri Alon, and Graham Neubig
    ICLR, 2024. project page

    • 2023

  • API-Assisted Code Generation for Question Answering on Varied Table Structures
    Yihan Cao*, Shuyi Chen*, Ryan Liu*, Zhiruo Wang, and Daniel Fried
    EMNLP, 2023.
  • Symbolic Planning and Code Generation for Grounded Dialogue
    Justin Chiu, Wenting Zhao, Derek Chen, Saujas Vaduguru, Alexander Rush, and Daniel Fried
    EMNLP, 2023.
  • Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
    Daniel Fried*, Nicholas Tomlin*, Jennifer Hu, Roma Patel, and Aida Nematzadeh
    Findings of EMNLP, 2023.
  • Execution-Based Evaluation for Open-Domain Code Generation
    Zhiruo Wang, Shuyan Zhou, Daniel Fried, and Graham Neubig
    Findings of EMNLP, 2023. dataset
  • Data Augmentation for Code Translation with Comparable Corpora and Multiple References
    Yiqing Xie, Atharva Naik, Daniel Fried, Carolyn Rose
    Findings of EMNLP, 2023.
  • AutoReply: Detecting Nonsense in Dialogue Introspectively with Discriminative Replies
    Weiyan Shi, Emily Dinan, Adi Renduchintala, Daniel Fried, Athul Paul Jacob, Zhou Yu, and Mike Lewis
    Findings of EMNLP, 2023.
  • Generating Images with Multimodal Language Models
    Jing Yu Koh, Daniel Fried, and Ruslan Salakhutdinov
    NeurIPS, 2023. project page
  • Pragmatic Inference with a CLIP Listener for Contrastive Captioning
    Jiefu Ou, Benno Krojer, and Daniel Fried
    Findings of ACL, 2023.
  • Contrastive Decoding: Open-ended Text Generation as Optimization
    Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, and Mike Lewis
    ACL, 2023. code
  • Grounding Language Models to Images for Multimodal Inputs and Outputs
    Jing Yu Koh, Ruslan Salakhutdinov, and Daniel Fried
    ICML, 2023. project page
  • Coder Reviewer Reranking for Code Generation
    Tianyi Zhang, Tao Yu, Tatsunori B. Hashimoto, Mike Lewis, Wen-tau Yih, Daniel Fried, and Sida I. Wang
    ICML, 2023. code
  • DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation
    Yuhang Lai*, Chengxi Li*, Yiming Wang*, Tianyi Zhang*, Ruiqi Zhong*, Luke Zettlemoyer, Scott Wen-tau Yih, Daniel Fried, Sida I. Wang, and Tao Yu
    ICML, 2023. site, code, data
  • InCoder: A Generative Model for Code Infilling and Synthesis
    Daniel Fried*, Armen Aghajanyan*, Jessy Lin, Sida I. Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis
    ICLR, 2023. site, code and models, demo
  • StarCoder: May the Source Be With You!
    Raymond Li et al. (68 authors from the BigCode Project)
    TMLR, 2023. project page, models, demo
  • SantaCoder: Don't Reach for the Stars
    Loubna Ben Allal*, Raymond Li*, Denis Kocetkov*, et al. (41 authors from the BigCode Project)
    Deep Learning for Code Workshop, 2023. models Best Paper Award

    • 2022

  • Natural Language to Code Translation with Execution
    Freda Shi, Daniel Fried, Marjan Ghazvininejad, Luke Zettlemoyer, and Sida I. Wang
    EMNLP, 2022. code
  • Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs
    Maarten Sap, Ronan Le Bras, Daniel Fried, and Yejin Choi
    EMNLP, 2022.
  • G3: Geolocation via Guidebook Grounding
    Grace Luo*, Giscard Biamby*, Trevor Darrell, Daniel Fried, and Anna Rohrbach
    Findings of EMNLP, 2022. code
  • Inferring Rewards from Language in Context
    Jessy Lin, Daniel Fried, Dan Klein, and Anca Dragan
    ACL, 2022. code and data
  • Human-Level Play in the Game of Diplomacy by Combining Language Models with Strategic Reasoning
    FAIR Diplomacy Team
    Science, 2022. site, code, blog, article
  • Modeling Perspective-Dependent Ambiguity in Grounded Collaborative Dialogue
    Justin Chiu, Wenting Zhao, Alexander M. Rush, and Daniel Fried
    Wordplay: When Language Meets Games Workshop, 2022.

    • 2021

  • Reference-Centric Models for Grounded Collaborative Dialogue
    Daniel Fried, Justin Chiu, and Dan Klein
    EMNLP, 2021. talk, slides [pdf], poster [pdf], code
  • Modular Networks for Compositional Instruction Following
    Rodolfo Corona, Daniel Fried, Coline Devin, Dan Klein, and Trevor Darrell
    NAACL, 2021.
  • Learning Grounded Pragmatic Communication
    Daniel Fried
    PhD thesis, 2021. job talk slides, video
  • Interactive Assignments for Teaching Structured Neural NLP
    David Gaddy, Daniel Fried, Nikita Kitaev, Mitchell Stern, Rodolfo Corona, John DeNero, and Dan Klein
    Teaching NLP Workshop at NAACL, 2021.

    • 2020 and before

  • Learning to Segment Actions from Observation and Narration
    Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh
    ACL, 2020. talk, slides [pdf], code
  • Syntactic Structure Distillation Pretraining for Bidirectional Encoders
    Adhiguna Kuncoro*, Lingpeng Kong*, Daniel Fried*, Dani Yogatama, Laura Rimell, Chris Dyer, and Phil Blunsom
    TACL, 2020. talk
  • Cross-Domain Generalization of Neural Constituency Parsers
    Daniel Fried*, Nikita Kitaev*, and Dan Klein
    ACL, 2019. talk, slides [pdf], code & models
  • Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation
    Ronghang Hu, Daniel Fried, Anna Rohrbach, Dan Klein, Trevor Darrell, and Kate Saenko
    ACL, 2019. poster [pdf]
  • Pragmatically Informative Text Generation
    Sheng Shen, Daniel Fried, Jacob Andreas, and Dan Klein
    NAACL, 2019. slides [pdf]
  • 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**, and Trevor Darrell**
    NeurIPS, 2018.
  • Policy Gradient as a Proxy for Dynamic Oracles in Constituency Parsing
    Daniel Fried and Dan Klein
    ACL, 2018. talk, slides [pptx], slides [pdf], code
  • Unified Pragmatic Models for Generating and Following Instructions
    Daniel Fried, Jacob Andreas, and Dan Klein
    NAACL, 2018. talk, slides [pptx], slides [pdf], code
  • Effective Inference for Generative Neural Parsing
    Mitchell Stern, Daniel Fried, and Dan Klein
    EMNLP, 2017. poster
  • Improving Neural Parsing by Disentangling Model Combination and Reranking Effects
    Daniel Fried*, Mitchell Stern*, and Dan Klein
    ACL, 2017. talk, slides [pptx], slides [pdf], code
  • Towards Using Social Media to Identify Individuals at Risk for Preventable Chronic Illness
    Dane Bell, Daniel Fried, Luwen Huangfu, Mihai Surdeanu, and Stephen Kobourov
    LREC, 2016.
  • Challenges for Using Social Media for Early Detection of Type II Diabetes Mellitus
    Dane Bell, Daniel Fried, Luwen Huangfu, Mihai Surdeanu, and Stephen Kobourov
    International Workshop on Social Media World Sensors, 2016.
  • Low-Rank Tensors for Verbs in Compositional Distributional Semantics
    Daniel Fried, Tamara Polajnar, and Stephen Clark
    ACL, 2015. poster [pdf]
  • Higher-Order Lexical Semantic Models for Non-Factoid Answer Reranking
    Daniel Fried, Peter Jansen, Gustave Hahn-Powell, Mihai Surdeanu, and Peter Clark
    TACL, 2015. slides [pdf]
  • Low-rank Tensor Approximations for Compositional Distributional Semantics
    Daniel Fried
    MPhil thesis, 2015.
  • Learning Low-Rank Tensors for Transitive Verbs
    Daniel Fried, Tamara Polajnar, and Stephen Clark
    Advances in Distributional Semantics Workshop, 2015.
  • Incorporating both Distributional and Relational Semantics in Word Representations
    Daniel Fried and Kevin Duh
    ICLR, 2015. long version [arxiv], poster [pdf]
  • Analyzing the Language of Food on Social Media
    Daniel Fried, Mihai Surdeanu, Stephen Kobourov, Melanie Hingle, and Dane Bell
    International Conference on Big Data, 2014. long version [arxiv], slides [pdf], demo
  • Maps of Computer Science
    Daniel Fried and Stephen Kobourov
    PacificVis, 2014. slides, poster, code, demo
  • Predicting Parallelization of Sequential Programs Using Supervised Learning
    Daniel Fried, Zhen Li, Ali Jannesari, and Felix Wolf
    International Conference on Machine Learning and Applications, 2013.
  • A Generative Probabilistic Framework for Learning Spatial Language
    Colin Dawson, Jeremy Wright, Antons Rebguns, Marco Valenzuela Escarcega, Daniel Fried, and Paul Cohen
    International Conference on Development and Learning, 2013. Best Paper Award
  • Bayesian Geometric Modeling of Indoor Scenes
    Luca Del Pero, Joshua Bowdish, Daniel Fried, Bonnie Kermgard, Emily Hartley, and Kobus Barnard
    CVPR, 2012.