Kyle Richardson

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 64

Top Topics

Semantic Parsing

Solve Complex Tasks

Top Venues

Publications

Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi
OLMo: Accelerating the Science of Language Models. CoRR (2024)
Yikai Zhang, Siyu Yuan, Caiyu Hu, Kyle Richardson, Yanghua Xiao, Jiangjie Chen
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation. CoRR (2024)
Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR (2024)
Dirk Groeneveld, Anas Awadalla, Iz Beltagy, Akshita Bhagia, Ian Magnusson, Hao Peng, Oyvind Tafjord, Pete Walsh, Kyle Richardson, Jesse Dodge
Catwalk: A Unified Language Model Evaluation Framework for Many Datasets. CoRR (2023)
Nora Kassner, Oyvind Tafjord, Ashish Sabharwal, Kyle Richardson, Hinrich Schütze, Peter Clark
Language Models with Rationality. EMNLP (2023)
Nora Kassner, Oyvind Tafjord, Ashish Sabharwal, Kyle Richardson, Hinrich Schütze, Peter Clark
Language Models with Rationality. CoRR (2023)
Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini, Ananya Harsh Jha, Oyvind Tafjord, Dustin Schwenk, Evan Pete Walsh, Yanai Elazar, Kyle Lo, Dirk Groeneveld, Iz Beltagy, Hannaneh Hajishirzi, Noah A. Smith, Kyle Richardson, Jesse Dodge
Paloma: A Benchmark for Evaluating Language Model Fit. CoRR (2023)
Jiangjie Chen, Siyu Yuan, Rong Ye, Bodhisattwa Prasad Majumder, Kyle Richardson
Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena. CoRR (2023)
Zeming Chen, Qiyue Gao, Antoine Bosselut, Ashish Sabharwal, Kyle Richardson
DISCO: Distilling Counterfactuals with Large Language Models. ACL (1) (2023)
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. ICLR (2023)
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. CoRR (2022)
Kyle Richardson, Ashish Sabharwal
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability. AAAI (2022)
Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment. CoRR (2022)
Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment. EMNLP (2022)
Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal
Hey AI, Can You Solve Complex Tasks by Talking to Agents? ACL (Findings) (2022)
Ronen Tamari, Kyle Richardson, Noam Kahlon, Aviad Sar-Shalom, Nelson F. Liu, Reut Tsarfaty, Dafna Shahaf
Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking. *SEM@NAACL-HLT (2022)
Zeming Chen, Qiyue Gao, Kyle Richardson, Antoine Bosselut, Ashish Sabharwal
DISCO: Distilling Phrasal Counterfactuals with Large Language Models. CoRR (2022)
Kyle Richardson, Ronen Tamari, Oren Sultan, Dafna Shahaf, Reut Tsarfaty, Ashish Sabharwal
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs. EMNLP (2022)
Gregor Betz, Kyle Richardson
Judgment aggregation, discursive dilemma and reflective equilibrium: Neural language models as self-improving doxastic agents. Frontiers Artif. Intell. 5 (2022)
Daniel Khashabi, Xinxi Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Sameer Singh, Yejin Choi
Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. NAACL-HLT (2022)
Kyle Richardson, Ronen Tamari, Oren Sultan, Reut Tsarfaty, Dafna Shahaf, Ashish Sabharwal
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs. CoRR (2022)
Ben Zhou, Kyle Richardson, Xiaodong Yu, Dan Roth
Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts. CoRR (2022)
Gregor Betz, Kyle Richardson
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models. *SEM@NAACL-HLT (2022)
Ben Zhou, Kyle Richardson, Xiaodong Yu, Dan Roth
Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts. EMNLP (2022)
Gregor Betz, Kyle Richardson, Christian Voigt
Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2. CoRR (2021)
Ben Zhou, Kyle Richardson, Qiang Ning, Tushar Khot, Ashish Sabharwal, Dan Roth
Temporal Reasoning on Implicit Events from Distant Supervision. NAACL-HLT (2021)
Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Yejin Choi
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts. CoRR (2021)
Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal
Learning to Solve Complex Tasks by Talking to Agents. CoRR (2021)
Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Peter Clark
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge. CoRR (2021)
Ronen Tamari, Kyle Richardson, Aviad Sar-Shalom, Noam Kahlon, Nelson F. Liu, Reut Tsarfaty, Dafna Shahaf
Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking. CoRR (2021)
Gregor Betz, Kyle Richardson
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models. CoRR (2021)
Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Ma, Yanting Li, Yixin Nie, Kyle Richardson
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference. CoRR (2021)
Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. NAACL-HLT (2021)
Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Patterson, Yanting Li, Yixin Nie, Kyle Richardson
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference. ACL/IJCNLP (Findings) (2021)
Kyle Richardson, Ashish Sabharwal
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability. CoRR (2021)
Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi Mishra, Dheeraj Rajagopal, Peter Clark, Michal Guerquin, Kyle Richardson, Eduard H. Hovy
A Dataset for Tracking Entities in Open Domain Procedural Text. CoRR (2020)
Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kübler, Lawrence S. Moss
OCNLI: Original Chinese Natural Language Inference. CoRR (2020)
Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. CoRR (2020)
Peter Clark, Oyvind Tafjord, Kyle Richardson
Transformers as Soft Reasoners over Language. IJCAI (2020)
Peter Clark, Oyvind Tafjord, Kyle Richardson
Transformers as Soft Reasoners over Language. CoRR (2020)
Sumithra Bhakthavatsalam, Kyle Richardson, Niket Tandon, Peter Clark
Do Dogs have Whiskers? A New Knowledge Base of hasPart Relations. CoRR (2020)
Peter Clark, Oren Etzioni, Tushar Khot, Daniel Khashabi, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project. AI Mag. 41 (4) (2020)
Atticus Geiger, Kyle Richardson, Christopher Potts
Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models. CoRR (2020)
Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi, Dheeraj Rajagopal, Peter Clark, Michal Guerquin, Kyle Richardson, Eduard H. Hovy
A Dataset for Tracking Entities in Open Domain Procedural Text. EMNLP (1) (2020)
Liang Xu, Hai Hu, Xuanwei Zhang, Lu Li, Chenjie Cao, Yudong Li, Yechen Xu, Kai Sun, Dian Yu, Cong Yu, Yin Tian, Qianqian Dong, Weitang Liu, Bo Shi, Yiming Cui, Junyi Li, Jun Zeng, Rongzhao Wang, Weijian Xie, Yanting Li, Yina Patterson, Zuoyu Tian, Yiwen Zhang, He Zhou, Shaoweihua Liu, Zhe Zhao, Qipeng Zhao, Cong Yue, Xinrui Zhang, Zhengliang Yang, Kyle Richardson, Zhenzhong Lan
CLUE: A Chinese Language Understanding Evaluation Benchmark. COLING (2020)
Atticus Geiger, Kyle Richardson, Christopher Potts
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation. BlackboxNLP@EMNLP (2020)
Kyle Richardson, Hai Hu, Lawrence S. Moss, Ashish Sabharwal
Probing Natural Language Inference Models through Semantic Fragments. AAAI (2020)
Ben Zhou, Kyle Richardson, Qiang Ning, Tushar Khot, Ashish Sabharwal, Dan Roth
Temporal Reasoning on Implicit Events from Distant Supervision. CoRR (2020)
Hai Hu, Kyle Richardson, Liang Xu, Lu Li, Sandra Kübler, Lawrence S. Moss
OCNLI: Original Chinese Natural Language Inference. EMNLP (Findings) (2020)
Kyle Richardson, Ashish Sabharwal
What Does My QA Model Know? Devising Controlled Probes using Expert. Trans. Assoc. Comput. Linguistics 8 (2020)
Kyle Richardson, Ashish Sabharwal
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge. CoRR (2019)
Kyle Richardson, Hai Hu, Lawrence S. Moss, Ashish Sabharwal
Probing Natural Language Inference Models through Semantic Fragments. CoRR (2019)
Hai Hu, Qi Chen, Kyle Richardson, Atreyee Mukherjee, Lawrence S. Moss, Sandra Kübler
MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity. CoRR (2019)
Peter Clark, Oren Etzioni, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project. CoRR (2019)
Kyle Richardson, Jonathan Berant, Jonas Kuhn
Polyglot Semantic Parsing in APIs. NAACL-HLT (2018)
Kyle Richardson
A Language for Function Signature Representations. CoRR (2018)
Kyle Richardson, Jonathan Berant, Jonas Kuhn
Polyglot Semantic Parsing in APIs. CoRR (2018)
Kyle Richardson, Jonas Kuhn
Function Assistant: A Tool for NL Querying of APIs. CoRR (2017)
Kyle Richardson, Jonas Kuhn
Learning Semantic Correspondences in Technical Documentation. ACL (1) (2017)
Kyle Richardson, Jonas Kuhn
Learning Semantic Correspondences in Technical Documentation. CoRR (2017)
Kyle Richardson, Sina Zarrieß, Jonas Kuhn
The Code2Text Challenge: Text Generation in Source Libraries. INLG (2017)
Kyle Richardson, Sina Zarrieß, Jonas Kuhn
The Code2Text Challenge: Text Generation in Source Code Libraries. CoRR (2017)
Kyle Richardson, Jonas Kuhn
Function Assistant: A Tool for NL Querying of APIs. EMNLP (System Demonstrations) (2017)
Cleo Condoravdi, Kyle Richardson, Vishal Sikka, Asuman Suenbuel, Richard Waldinger
Natural Language Access to Data: It Takes Common Sense! AAAI Spring Symposia (2015)
Kyle Richardson, Jonas Kuhn
UnixMan Corpus: A Resource for Language Learning in the Unix Domain. LREC (2014)
Sina Zarrieß, Kyle Richardson
An Automatic Method for Building a Data-to-Text Generator. ENLG (2013)
Kyle Richardson, Jonas Kuhn
Light Textual Inference for Semantic Parsing. COLING (Posters) (2012)
Richard J. Waldinger, Daniel G. Bobrow, Cleo Condoravdi, Kyle Richardson, Amar Das
Accessing Structured Health Information through English Queries and Automatic Deduction. AAAI Spring Symposium: AI and Health Communication (2011)
Daniel G. Bobrow, Cleo Condoravdi, Kyle Richardson, Richard J. Waldinger, Amar Das
Deducing answers to english questions from structured data. IUI (2011)
Kyle Richardson, Daniel G. Bobrow, Cleo Condoravdi, Richard J. Waldinger, Amar Das
English Access to Structured Data. ICSC (2011)