Kyle Richardson
Affiliations:- Allen Institute for AI, Seattle, WA, USA
According to our database1,
Kyle Richardson
authored at least 61 papers
between 2011 and 2024.
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Bibliography
2024
CoRR, 2024
SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.
Trans. Mach. Learn. Res., 2023
Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena.
CoRR, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
2022
Judgment aggregation, discursive dilemma and reflective equilibrium: Neural language models as self-improving doxastic agents.
Frontiers Artif. Intell., 2022
Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, 2022
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language Models.
Proceedings of the 11th Joint Conference on Lexical and Computational Semantics, 2022
Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts.
CoRR, 2021
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference.
CoRR, 2021
Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2.
CoRR, 2021
Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge.
CoRR, 2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021
2020
Trans. Assoc. Comput. Linguistics, 2020
Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models.
CoRR, 2020
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project.
AI Mag., 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
Proceedings of the 28th International Conference on Computational Linguistics, 2020
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation.
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
CoRR, 2019
CoRR, 2019
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018
2017
Proceedings of the 10th International Conference on Natural Language Generation, 2017
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017
2016
Trans. Assoc. Comput. Linguistics, 2016
2015
Proceedings of the 2015 AAAI Spring Symposia, 2015
2014
Proceedings of the Ninth International Conference on Language Resources and Evaluation, 2014
2013
Proceedings of the ENLG 2013, 2013
2012
2011
Proceedings of the 5th IEEE International Conference on Semantic Computing (ICSC 2011), 2011
Proceedings of the 16th International Conference on Intelligent User Interfaces, 2011
Accessing Structured Health Information through English Queries and Automatic Deduction.
Proceedings of the AI and Health Communication, 2011