Kyle Richardson

Affiliations:
  • Allen Institute for AI, Seattle, WA, USA


According to our database1, Kyle Richardson authored at least 55 papers between 2011 and 2024.

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Bibliography

2024
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation.
CoRR, 2024

OLMo: Accelerating the Science of Language Models.
CoRR, 2024

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
CoRR, 2024

2023
Paloma: A Benchmark for Evaluating Language Model Fit.
CoRR, 2023

Catwalk: A Unified Language Model Evaluation Framework for Many Datasets.
CoRR, 2023

Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena.
CoRR, 2023

Decomposed Prompting: A Modular Approach for Solving Complex Tasks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Language Models with Rationality.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

DISCO: Distilling Counterfactuals with Large Language Models.
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

DISCO: Distilling Phrasal Counterfactuals with Large Language Models.
CoRR, 2022

Dyna-bAbI: unlocking bAbI's potential with dynamic synthetic benchmarking.
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

Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Hey AI, Can You Solve Complex Tasks by Talking to Agents?
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

Learning to Solve Complex Tasks by Talking to Agents.
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

Temporal Reasoning on Implicit Events from Distant Supervision.
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
What Does My QA Model Know? Devising Controlled Probes using Expert.
Trans. Assoc. Comput. Linguistics, 2020

OCNLI: Original Chinese Natural Language Inference.
CoRR, 2020

Do Dogs have Whiskers? A New Knowledge Base of hasPart Relations.
CoRR, 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

Transformers as Soft Reasoners over Language.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

A Dataset for Tracking Entities in Open Domain Procedural Text.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

OCNLI: Original Chinese Natural Language Inference.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 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

Probing Natural Language Inference Models through Semantic Fragments.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
What Does My QA Model Know? Devising Controlled Probes using Expert Knowledge.
CoRR, 2019

MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity.
CoRR, 2019

2018
New resources and ideas for semantic parser induction.
PhD thesis, 2018

A Language for Function Signature Representations.
CoRR, 2018

Polyglot Semantic Parsing in APIs.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2017
The Code2Text Challenge: Text Generation in Source Code Libraries.
CoRR, 2017

The Code2Text Challenge: Text Generation in Source Libraries.
Proceedings of the 10th International Conference on Natural Language Generation, 2017

Function Assistant: A Tool for NL Querying of APIs.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Learning Semantic Correspondences in Technical Documentation.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016
Learning to Make Inferences in a Semantic Parsing Task.
Trans. Assoc. Comput. Linguistics, 2016

2015
Natural Language Access to Data: It Takes Common Sense!
Proceedings of the 2015 AAAI Spring Symposia, 2015

2014
UnixMan Corpus: A Resource for Language Learning in the Unix Domain.
Proceedings of the Ninth International Conference on Language Resources and Evaluation, 2014

2013
An Automatic Method for Building a Data-to-Text Generator.
Proceedings of the ENLG 2013, 2013

2012
Light Textual Inference for Semantic Parsing.
Proceedings of the COLING 2012, 2012

2011
English Access to Structured Data.
Proceedings of the 5th IEEE International Conference on Semantic Computing (ICSC 2011), 2011

Deducing answers to english questions from structured data.
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


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