Christopher Potts

26.4k total citations · 5 hit papers
116 papers, 10.6k citations indexed

About

Christopher Potts is a scholar working on Artificial Intelligence, Language and Linguistics and Experimental and Cognitive Psychology. According to data from OpenAlex, Christopher Potts has authored 116 papers receiving a total of 10.6k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Artificial Intelligence, 29 papers in Language and Linguistics and 14 papers in Experimental and Cognitive Psychology. Recurrent topics in Christopher Potts's work include Natural Language Processing Techniques (59 papers), Topic Modeling (43 papers) and Syntax, Semantics, Linguistic Variation (25 papers). Christopher Potts is often cited by papers focused on Natural Language Processing Techniques (59 papers), Topic Modeling (43 papers) and Syntax, Semantics, Linguistic Variation (25 papers). Christopher Potts collaborates with scholars based in United States, Belgium and United Kingdom. Christopher Potts's co-authors include Christopher D. Manning, Andrew Y. Ng, Richard Socher, Jason Chuang, Jean Y. Wu, Samuel R. Bowman, Gabor Angeli, Andrew L. Maas, Dan Huang and Jure Leskovec and has published in prestigious journals such as Nature Neuroscience, American Sociological Review and Management Science.

In The Last Decade

Christopher Potts

106 papers receiving 9.5k citations

Hit Papers

Recursive Deep Models for... 2004 2026 2011 2018 2013 2011 2015 2004 2007 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
    2013 3.7k citations Richard Socher, Jean Y. Wu et al. profile →
  2. Learning Word Vectors for Sentiment Analysis
    2011 1.8k citations Andrew L. Maas, Dan Huang et al. Meeting of the Association for Computational Linguistics profile →
  3. A large annotated corpus for learning natural language inference
    2015 1.8k citations Samuel R. Bowman, Christopher Potts et al. profile →
  4. The Logic of Conventional Implicatures
    2004 654 citations Christopher Potts profile →
  5. The expressive dimension
    2007 354 citations Christopher Potts profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Christopher Potts 8.3k 1.4k 1.4k 957 828 116 10.6k
Adam Kilgarriff 9.4k 1.1× 2.0k 1.4× 954 0.7× 1.7k 1.7× 674 0.8× 111 11.9k
Ewan Klein 3.6k 0.4× 1.4k 1.0× 372 0.3× 624 0.7× 636 0.8× 92 5.7k
Daniel Jurafsky 8.7k 1.0× 908 0.6× 776 0.6× 1.2k 1.2× 955 1.2× 95 10.9k
Dan Jurafsky 9.9k 1.2× 569 0.4× 1.2k 0.9× 1.4k 1.4× 1.0k 1.3× 203 13.5k
Mark Steedman 6.4k 0.8× 1.8k 1.2× 1.2k 0.9× 362 0.4× 1.2k 1.5× 209 9.3k
James Pustejovsky 6.0k 0.7× 2.0k 1.4× 305 0.2× 462 0.5× 1.0k 1.2× 219 7.9k
Julia Hirschberg 7.8k 0.9× 2.3k 1.6× 661 0.5× 697 0.7× 4.3k 5.2× 324 12.1k
Steven Bird 4.9k 0.6× 426 0.3× 689 0.5× 1.2k 1.3× 366 0.4× 134 6.8k
Marco Baroni 5.8k 0.7× 630 0.4× 870 0.6× 390 0.4× 547 0.7× 128 7.0k
Barbara J. Grosz 4.2k 0.5× 969 0.7× 223 0.2× 325 0.3× 1.0k 1.2× 119 6.3k

Countries citing papers authored by Christopher Potts

Since Specialization
Citations

This map shows the geographic impact of Christopher Potts'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 Christopher Potts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Potts more than expected).

Fields of papers citing papers by Christopher Potts

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher Potts. 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 Christopher Potts. The network helps show where Christopher Potts may publish in the future.

Co-authorship network of co-authors of Christopher Potts

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Potts. A scholar is included among the top collaborators of Christopher Potts 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 Christopher Potts. Christopher Potts is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liang, Weixin, Zhengxuan Wu, Hancheng Cao, et al.. (2025). Quantifying large language model usage in scientific papers. Nature Human Behaviour. 9(12). 2599–2609. 8 indexed citations
2.
Gupta, Varun, Christopher Potts, Hongpeng Gao, et al.. (2025). Streamlining Ni‐Rich LiNi x Mn y Co z O 2 Cathode Black Mass Purification for Direct Recycling and Upcycling through the Alkoxythermal Process. Advanced Energy Materials. 15(46). 5 indexed citations
3.
Potts, Christopher, et al.. (2024). Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together. 10696–10710. 2 indexed citations
4.
Thrush, Tristan, et al.. (2024). I am a Strange Dataset: Metalinguistic Tests for Language Models. 8888–8907.
5.
Khattab, Omar, et al.. (2024). Building efficient and effective OpenQA systems for low-resource languages. Knowledge-Based Systems. 302. 112243–112243. 3 indexed citations
6.
Jurafsky, Dan, et al.. (2024). CausalGym: Benchmarking causal interpretability methods on linguistic tasks. 14638–14663. 2 indexed citations
7.
Papadimitriou, Isabel, et al.. (2024). Mission: Impossible Language Models. 14691–14714. 7 indexed citations
8.
Zhang, Jingfen, et al.. (2023). Multi-teacher Distillation for Multilingual Spelling Correction. 142–151.
9.
Wu, Zhengxuan, et al.. (2023). Rigorously Assessing Natural Language Explanations of Neurons. 317–331.
10.
Remy, François, Johannes Deleu, Thomas Demeester, et al.. (2023). BioDEX: Large-Scale Biomedical Adverse Drug Event Extraction for Real-World Pharmacovigilance. 13425–13454. 1 indexed citations
11.
Fang, Fei, et al.. (2022). Concadia: Towards Image-Based Text Generation with a Purpose. 4667–4684. 8 indexed citations
12.
Bowman, Samuel R., Jon Gauthier, Abhinav Rastogi, et al.. (2016). A Fast Unified Model for Parsing and Sentence Understanding. 1466–1477. 139 indexed citations
13.
Potts, Christopher. (2015). On the negativity of negation. Proceedings from Semantics and Linguistic Theory. 636–636. 1 indexed citations
14.
Vogel, Adam P., et al.. (2014). Learning to Reason Pragmatically with Cognitive Limitations. Cognitive Science. 36(36). 4 indexed citations
15.
Socher, Richard, Jean Y. Wu, Jason Chuang, et al.. (2013). Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. 1631–1642. 3653 indexed citations breakdown →
16.
Vogel, Adam P., et al.. (2013). Emergence of Gricean Maxims from Multi-Agent Decision Theory. North American Chapter of the Association for Computational Linguistics. 1072–1081. 23 indexed citations
17.
Maas, Andrew L., et al.. (2011). Learning Word Vectors for Sentiment Analysis. Meeting of the Association for Computational Linguistics. 142–150. 1805 indexed citations breakdown →
18.
Munro, Robert, Steven Bethard, Victor Kuperman, et al.. (2010). Crowdsourcing and language studies: the new generation of linguistic data. Max Planck Digital Library. 122–130. 94 indexed citations
19.
Mikkelsen, Line & Christopher Potts. (2002). WCCFL 21 : proceedings of the 21st West Coast Conference on Formal Linguistics. 18 indexed citations
20.
Quintana, Chris, Joseph Krajcik, Elliot Soloway, et al.. (2001). Learner-Centered Design: Reflections and New Directions. Human-Computer Interaction. 16(1). 605–626. 31 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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