Traversing Knowledge Graphs in Vector Space. - Kelvin Guu; John Miller 001; Percy Liang (EMNLP, 2015)

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood. - Kelvin Guu; Panupong Pasupat; Evan Zheran Liu; Percy Liang (ACL (1), 2017)

Mapping natural language commands to web elements. - Panupong Pasupat; Tian-Shun Jiang; Evan Zheran Liu; Kelvin Guu; Percy Liang (EMNLP, 2018)

Reinforcement Learning on Web Interfaces using Workflow-Guided Exploration. - Evan Zheran Liu; Kelvin Guu; Panupong Pasupat; Tianlin Shi; Percy Liang (ICLR (Poster), 2018)

A Retrieve-and-Edit Framework for Predicting Structured Outputs. - Tatsunori B. Hashimoto; Kelvin Guu; Yonatan Oren; Percy Liang (NeurIPS, 2018)

Transforming Question Answering Datasets Into Natural Language Inference Datasets. - Dorottya Demszky; Kelvin Guu; Percy Liang (CoRR, 2018)

Generating Sentences by Editing Prototypes. - Kelvin Guu; Tatsunori B. Hashimoto; Yonatan Oren; Percy Liang (Trans. Assoc. Comput. Linguistics, 2018)

KERMIT: Generative Insertion-Based Modeling for Sequences. - William Chan; Nikita Kitaev; Kelvin Guu; Mitchell Stern; Jakob Uszkoreit (CoRR, 2019)

Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. - Dan Iter; Kelvin Guu; Larry Lansing; Dan Jurafsky (ACL, 2020)

Retrieval Augmented Language Model Pre-Training. - Kelvin Guu; Kenton Lee; Zora Tung; Panupong Pasupat; Ming-Wei Chang (ICML, 2020)

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. - Sewon Min; Jordan L. Boyd-Graber; Chris Alberti; Danqi Chen 001; Eunsol Choi; Michael Collins 001; Kelvin Guu; Hannaneh Hajishirzi; Kenton Lee; Jennimaria Palomaki; Colin Raffel; Adam Roberts; et al. (NeurIPS (Competition and Demos), 2020)

REALM: Retrieval-Augmented Language Model Pre-Training. - Kelvin Guu; Kenton Lee; Zora Tung; Panupong Pasupat; Ming-Wei Chang (CoRR, 2020)

Learning Abstract Models for Strategic Exploration and Fast Reward Transfer. - Evan Zheran Liu; Ramtin Keramati; Sudarshan Seshadri; Kelvin Guu; Panupong Pasupat; Emma Brunskill; Percy Liang (CoRR, 2020)

Controllable Semantic Parsing via Retrieval Augmentation. - Panupong Pasupat; Yuan Zhang 001; Kelvin Guu (EMNLP (1), 2021)

Neural Data Augmentation via Example Extrapolation. - Kenton Lee; Kelvin Guu; Luheng He; Tim Dozat; Hyung Won Chung (CoRR, 2021)

Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations. - Jonathan Herzig; Peter Shaw 004; Ming-Wei Chang; Kelvin Guu; Panupong Pasupat; Yuan Zhang 001 (CoRR, 2021)

Towards Tracing Knowledge in Language Models Back to the Training Data. - Ekin Akyürek; Tolga Bolukbasi; Frederick Liu; Binbin Xiong; Ian Tenney; Jacob Andreas; Kelvin Guu (EMNLP (Findings), 2022)

Meta-Learning Fast Weight Language Models. - Kevin Clark; Kelvin Guu; Ming-Wei Chang; Panupong Pasupat; Geoffrey E. Hinton; Mohammad Norouzi 002 (EMNLP, 2022)

Finetuned Language Models are Zero-Shot Learners. - Jason Wei; Maarten Bosma; Vincent Y. Zhao; Kelvin Guu; Adams Wei Yu; Brian Lester; Nan Du 002; Andrew M. Dai; Quoc V. Le (ICLR, 2022)

Dialog Inpainting: Turning Documents into Dialogs. - Zhuyun Dai; Arun Tejasvi Chaganty; Vincent Y. Zhao; Aida Amini; Qazi Mamunur Rashid; Mike Green; Kelvin Guu (ICML, 2022)

Tracing Knowledge in Language Models Back to the Training Data. - Ekin Akyürek; Tolga Bolukbasi; Frederick Liu; Binbin Xiong; Ian Tenney; Jacob Andreas; Kelvin Guu (CoRR, 2022)

Attributed Text Generation via Post-hoc Research and Revision. - Luyu Gao; Zhuyun Dai; Panupong Pasupat; Anthony Chen; Arun Tejasvi Chaganty; Yicheng Fan; Vincent Y. Zhao; Ni Lao; Hongrae Lee; Da-Cheng Juan; Kelvin Guu (CoRR, 2022)

RARR: Researching and Revising What Language Models Say, Using Language Models. - Luyu Gao; Zhuyun Dai; Panupong Pasupat; Anthony Chen; Arun Tejasvi Chaganty; Yicheng Fan; Vincent Y. Zhao; Ni Lao; Hongrae Lee; Da-Cheng Juan; Kelvin Guu (ACL (1), 2023)

Promptagator: Few-shot Dense Retrieval From 8 Examples. - Zhuyun Dai; Vincent Y. Zhao; Ji Ma 004; Yi Luan; Jianmo Ni; Jing Lu; Anton Bakalov; Kelvin Guu; Keith B. Hall; Ming-Wei Chang (ICLR, 2023)

Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs. - Kelvin Guu; Albert Webson; Ellie Pavlick; Lucas Dixon; Ian Tenney; Tolga Bolukbasi (CoRR, 2023)

PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions. - Anthony Chen; Panupong Pasupat; Sameer Singh 001; Hongrae Lee; Kelvin Guu (CoRR, 2023)

Few-Shot Recalibration of Language Models. - Xiang Lisa Li; Urvashi Khandelwal; Kelvin Guu (CoRR, 2024)

Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (CoRR, 2024)

LOFT: Scalable and More Realistic Long-Context Evaluation. - Jinhyuk Lee; Anthony Chen; Zhuyun Dai; Dheeru Dua; Devendra Singh Sachan; Michael Boratko; Yi Luan; Sébastien M. R. Arnold; Vincent Perot; Siddharth Dalmia; Hexiang Hu; Xudong Lin 008; et al. (NAACL (Findings), 2025)

Towards physician-centered oversight of conversational diagnostic AI. - Elahe Vedadi; David G. T. Barrett; Natalie Harris; Ellery Wulczyn; Shashir Reddy; Roma Ruparel; Mike Schaekermann; Tim Strother; Ryutaro Tanno; Yash Sharma; Jihyeon Lee; Cían Hughes; et al. (CoRR, 2025)