Kyle Richardson

2.4k total citations
74 papers, 787 citations indexed

About

Kyle Richardson is a scholar working on Clinical Psychology, Social Psychology and Artificial Intelligence. According to data from OpenAlex, Kyle Richardson has authored 74 papers receiving a total of 787 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Clinical Psychology, 26 papers in Social Psychology and 26 papers in Artificial Intelligence. Recurrent topics in Kyle Richardson's work include Personality Traits and Psychology (32 papers), Natural Language Processing Techniques (22 papers) and Topic Modeling (20 papers). Kyle Richardson is often cited by papers focused on Personality Traits and Psychology (32 papers), Natural Language Processing Techniques (22 papers) and Topic Modeling (20 papers). Kyle Richardson collaborates with scholars based in United States, Germany and Switzerland. Kyle Richardson's co-authors include William Hart, Gregory K. Tortoriello, Christopher J. Breeden, Thomas E. Ford, Ashish Sabharwal, Alexa M. Tullett, John M. Adams, Tushar Khot, Hai Hu and Sandra Kübler and has published in prestigious journals such as PLoS ONE, Journal of Allergy and Clinical Immunology and Personality and Social Psychology Bulletin.

In The Last Decade

Kyle Richardson

71 papers receiving 760 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kyle Richardson United States	18	353	298	210	189	140	74	787
Jonathan E. Ramsay Singapore	14	142 0.4×	258 0.9×	317 1.5×	77 0.4×	100 0.7×	26	668
Lesa A. Stern United States	9	88 0.2×	447 1.5×	241 1.1×	75 0.4×	152 1.1×	12	810
Janet Walker United States	8	88 0.2×	167 0.6×	150 0.7×	103 0.5×	54 0.4×	18	468
Hyisung C. Hwang United States	14	85 0.2×	362 1.2×	237 1.1×	62 0.3×	106 0.8×	36	653
Leesa Dillman United States	5	106 0.3×	550 1.8×	289 1.4×	98 0.5×	153 1.1×	5	779
Jordan Carpenter United States	12	85 0.2×	139 0.5×	214 1.0×	99 0.5×	74 0.5×	20	485
Michael Laakasuo Finland	18	199 0.6×	187 0.6×	152 0.7×	63 0.3×	68 0.5×	48	671
Bingjie Liu United States	13	77 0.2×	215 0.7×	384 1.8×	319 1.7×	59 0.4×	27	790
Aijaz Ahmed Gujjar Pakistan	9	84 0.2×	173 0.6×	124 0.6×	30 0.2×	118 0.8×	39	778
T. Makana Chock United States	16	196 0.6×	77 0.3×	478 2.3×	65 0.3×	49 0.3×	27	769

Countries citing papers authored by Kyle Richardson

Since Specialization

Citations

This map shows the geographic impact of Kyle Richardson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kyle Richardson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Richardson more than expected).

Fields of papers citing papers by Kyle Richardson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kyle Richardson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kyle Richardson. The network helps show where Kyle Richardson may publish in the future.

Co-authorship network of co-authors of Kyle Richardson

This figure shows the co-authorship network connecting the top 25 collaborators of Kyle Richardson. A scholar is included among the top collaborators of Kyle Richardson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kyle Richardson. Kyle Richardson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bogin, Ben, Shashank Gupta, Kyle Richardson, et al.. (2024). SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories. 12622–12645. 1 indexed citations

Wang, Haoyu, et al.. (2024). Event Causality Identification with Synthetic Control. ArXiv.org. 1725–1737. 1 indexed citations

Kassner, Nora, Oyvind Tafjord, Ashish Sabharwal, et al.. (2023). Language Models with Rationality. 2 indexed citations

Chen, Zeming, Qiyue Gao, Antoine Bosselut, Ashish Sabharwal, & Kyle Richardson. (2023). DISCO: Distilling Counterfactuals with Large Language Models. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 5514–5528. 11 indexed citations

Finlayson, Matthew, Kyle Richardson, Ashish Sabharwal, & Peter Clark. (2022). What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment. 414–426. 5 indexed citations

Richardson, Kyle, et al.. (2022). Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs. 9703–9719. 2 indexed citations

Khashabi, Daniel, Xinxi Lyu, Sewon Min, et al.. (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. 3631–3643. 22 indexed citations

Betz, Gregor & Kyle Richardson. (2022). Judgment aggregation, discursive dilemma and reflective equilibrium: Neural language models as self-improving doxastic agents. Frontiers in Artificial Intelligence. 5. 900943–900943. 1 indexed citations

Zhou, Ben, Kyle Richardson, Xiaodong Yu, & Dan Roth. (2022). Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts. 2223–2235. 7 indexed citations

10.

Hu, Hai, et al.. (2021). Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference. 3770–3785. 8 indexed citations

11.

Hart, William, et al.. (2021). We are who we thought we were: Confirming one’s own antagonism levels.. Personality Disorders Theory Research and Treatment. 13(2). 133–143. 9 indexed citations

12.

Tandon, Niket, Keisuke Sakaguchi, Bhavana Dalvi, et al.. (2020). A Dataset for Tracking Entities in Open Domain Procedural Text. 6408–6417. 22 indexed citations

13.

Richardson, Kyle, et al.. (2020). Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models. arXiv (Cornell University). 1 indexed citations

14.

Hu, Hai, et al.. (2020). OCNLI: Original Chinese Natural Language Inference. 3512–3526. 38 indexed citations

15.

Ford, Thomas E., Tracey Platt, Kyle Richardson, & Raymond P. Tucker. (2016). The psychology of humor: Basic research and translation.. Translational Issues in Psychological Science. 2(1). 1–3. 5 indexed citations

16.

Ford, Thomas E., et al.. (2016). Putting the brakes on prejudice rebound effects: An ironic effect of disparagement humor. The Journal of Social Psychology. 157(4). 458–473. 7 indexed citations

17.

Ford, Thomas E., et al.. (2015). Disparagement humor and prejudice: Contemporary theory and research. Humor - International Journal of Humor Research. 28(2). 25 indexed citations

18.

Ford, Thomas E., et al.. (2015). Sexist humor as a trigger of state self-objectification in women. Humor - International Journal of Humor Research. 28(2). 21 indexed citations

19.

Richardson, Kyle & Jonas Kuhn. (2012). Light Textual Inference for Semantic Parsing. International Conference on Computational Linguistics. 1007–1018. 2 indexed citations

20.

Waldinger, Richard, Daniel G. Bobrow, Cleo Condoravdi, Kyle Richardson, & Amar K. Das. (2011). Accessing Structured Health Information through English Queries and Automatic Deduction. National Conference on Artificial Intelligence. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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