🧑‍🔬 Christopher E. Potts

🏛️ Affiliations

🎓Stanford UniversityStanford · United States2007–2026 · 212 papersEmployment · Professor, Linguisticscurrent🎓University of Massachusetts AmherstAmherst Center · United States2003–2015 · 12 papers🎓University of California, Santa CruzSanta Cruz · United States2002 · 3 papers🎓University of California San DiegoSan Diego · United States2015–2024 · 2 papers🏢GoogleMountain View · United States2015–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

2010s

2000s

📄 Papers

The most cited first (OpenAlex and our library).

1 2 next →

1. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank (2013 · 9,138 citations)
   Vectors of individual words poorly capture the meaning of longer phrases. Studying how the sentiment of a sentence is composed from its parts was hampered by a lack of large annotated resources. The authors created the Stanford Sentiment Treebank. They took a corpus of short movie review excerpts from…
2. A large annotated corpus for learning natural language inference (2015 · 5,299 citations)
   The paper addresses the task of natural language inference (NLI). The goal is to determine whether the second sentence follows from the first, contradicts it, or is unrelated to it. The authors note that existing corpora for this task suffer from three shortcomings. They are too small for modern models, some of them…
3. Learning Word Vectors for Sentiment Analysis (2011 · 4,333 citations)
   Word vectors learned without supervision capture topical similarity well but mostly ignore sentiment. Words such as wonderful and terrible can end up close together because they appear in similar contexts. Maas et al. propose a model that learns word vectors from two signals at once. The first is an unsupervised…
4. ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction (2022 · 485 citations)
   Late interaction retrievers such as ColBERT give every query and passage token its own vector. They score relevance by letting each query token find its best-matching passage token and then adding up those matches. This is more expressive than compressing a whole text into one vector. The cost is size: storing a…
5. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP (2022 · 222 citations)
   Pairing a frozen language model with a retriever usually follows a fixed recipe: fetch passages for the query, insert them into the prompt, and let the model answer.
6. Did It Happen? The Pragmatic Complexity of Veridicality Assessment (2012 · 202 citations)
   Event and relation extraction systems usually treat any relation they extract as true. They largely ignore veridicality, meaning whether a reader takes a described event to have actually happened. Earlier work mostly treated veridicality as a fixed lexical property, such as believe being non-veridical or realize…
7. The Life and Death of Discourse Entities: Identifying Singleton Mentions (2013 · 166 citations)
   Most entities introduced in a text are mentioned only once. The authors ask whether such one-off mentions (singletons) can be told apart from mentions that join a coreference chain, using only properties of the noun phrase and its context. They use the CoNLL-2012 Shared Task portion of OntoNotes v5.0. Because…
8. Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding (2017 · 156 citations)
   The paper asks how a system can interpret color descriptions as people do, taking into account which other colors appear alongside the target.
9. A computational approach to politeness with application to social factors (2013 · 141 citations)
   The paper addresses how to detect politeness in text automatically. It focuses on requests, because asking something of another person is an imposition and tends to trigger politeness strategies. The authors collected requests from Wikipedia user talk-pages and Stack Exchange comments. They had a subset rated on…
10. Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation (2020 · 123 citations)
    The question is whether neural NLI models learn how negation reverses lexical entailment: "dance" entails "move", but "not move" does not entail "not dance".
11. Relevance-guided Supervision for OpenQA with ColBERT (2021 · 121 citations)
    Open-domain question answering (OpenQA) systems pair a retriever with a reader. Learned retrievers such as DPR, ORQA and REALM compress each passage and question into one vector. The authors argue this is too coarse for complex questions, and that current supervision is costly or brittle. Some methods need…
12. Pragmatically Informative Image Captioning with Character-Level Inference (2018 · 103 citations)
    Standard neural image captioners describe an image accurately but often fail to say what sets it apart from similar pictures.
13. Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs (2024 · 99 citations)
    Pipelines that chain several language model calls (LM programs) need prompts that work well together across all stages.
14. Interpretability at Scale: Identifying Causal Mechanisms in Alpaca (2023 · 81 citations)
    Causal-abstraction methods test whether a neural network actually implements a human-readable algorithm, but until now they had only been applied to small, task-specific models.
15. Learning in the Rational Speech Acts Model (2015 · 78 citations)
    The Rational Speech Acts (RSA) model describes pragmatics: the speaker and the listener recursively model each other's intentions and thereby enrich the literal meaning of utterances.
16. Mission: Impossible Language Models (2024 · 70 citations)
    Chomsky and colleagues have argued that LLMs pick up languages humans could never acquire just as readily as natural ones, but almost no experiments have tested this.
17. Posing Fair Generalization Tasks for Natural Language Inference (2019 · 61 citations)
    Adversarial and synthetic test sets often show that NLI models with strong scores on naturalistic corpora break down on systematic cases.
18. Was It Good? It Was Provocative.” Learning the Meaning of Scalar Adjectives (2010 · 56 citations)
    Indirect answers to yes/no questions often do not say "yes" or "no" outright. "Was it good? It was provocative" leaves the answer open, while "It was great" does not. The authors mine two kinds of evidence. First, scale order between gradable adjectives comes from online IMDB reviews: a word's expected star rating…
19. Representing Social Media Users for Sarcasm Detection (2018 · 54 citations)
    Sarcasm is hard to detect from text alone because the same words can be literal or ironic depending on context.
20. Emergence of Gricean Maxims from Multi-Agent Decision Theory (2013 · 51 citations)
    Grice's cooperative principle and maxims (quality, relation, quantity, manner) are usually stated as norms.
21. Implicatures and Nested Beliefs in Approximate Decentralized-POMDPs (2013 · 45 citations)
    Gricean implicatures require agents to reason about what others believe about their own beliefs. Such nested reasoning is hard to model computationally. Vogel, Potts and Jurafsky treat communication as a decision problem inside a Decentralized-POMDP (Dec-POMDP), in which two agents share a reward. Exact Dec-POMDP…
22. CausalGym: Benchmarking causal interpretability methods on linguistic tasks (2024 · 38 citations)
    CausalGym connects two research lines that have mostly stayed apart. Psycholinguistic work tests language models on large behavioural benchmarks. Interpretability work tries to find internal causal mechanisms but usually evaluates on small, one-off datasets. The authors turn SyntaxGym test suites into templates that…
23. Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences (2018 · 37 citations)
    Benchmarks built from naturalistic NLI corpora say little about how much compositional meaning a model actually captures, because their examples have no reliable measure of semantic difficulty.
24. An Incremental Iterated Response Model of Pragmatics (2019 · 35 citations)
    Rational Speech Acts (RSA) and other Iterated Response (IR) models treat pragmatics as speakers and listeners recursively reasoning about one another.
25. Rigorously Assessing Natural Language Explanations of Neurons (2023 · 30 citations)
    Natural-language descriptions of what individual neurons in large language models encode are appealing, but it is unclear whether they faithfully reflect model behavior.

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All works

270 works of theirs in our library, the most cited first; 33 with a page here, the others link their original until we summarise them.

1. Recursive Deep Models for Semantic Compositionality Over a Sentiment TreebankConference on Empirical Methods in Natural Language Processing (EMNLP)Richard Socher, Alex Perelygin, Jean Wu, et al.2013 · 9,138 citations
2. A large annotated corpus for learning natural language inferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Samuel R. Bowman, Gabor Angeli, Christopher Potts, et al.2015 · 5,299 citations
3. Learning Word Vectors for Sentiment AnalysisAnnual Meeting of the Association for Computational Linguistics (ACL)Andrew L. Maas, Raymond E. Daly, Peter T. Pham, et al.2011 · 4,333 citations
4. The Logic of Conventional Implicatures ↗Oxford University Press (book) · no summary yetChristopher Potts2005 · 1,401 citations
5. A logic for conventional implicatures ↗Oxford University Press eBooks · no summary yetChristopher E. Potts2004 · 908 citations
6. The expressive dimension ↗Theoretical Linguistics · no summary yetChristopher Potts2007 · 789 citations
7. ColBERTv2: Effective and Efficient Retrieval via Lightweight Late InteractionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, et al.2022 · 485 citations
8. Dynabench: Rethinking Benchmarking in NLP ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetDouwe Kiela et al.2021 · 482 citations
9. No country for old members ↗International World Wide Web Conference (WWW) · no summary yetCristian Danescu-Niculescu-Mizil et al.2013 · 342 citations
10. A Fast Unified Model for Parsing and Sentence Understanding ↗Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetSamuel R. Bowman et al.2016 · 323 citations
11. Perspective-shifting with appositives and expressives ↗Linguistics and Philosophy · no summary yetJesse A. Harris, Christopher E. Potts2009 · 263 citations
12. Exploiting Social Network Structure for Person-to-Person Sentiment Analysis ↗Transactions of the Association for Computational Linguistics · no summary yetRobert West et al.2014 · 224 citations
13. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
14. Did It Happen? The Pragmatic Complexity of Veridicality AssessmentComputational LinguisticsMarie-Catherine de Marneffe, Christopher D. Manning, Christopher Potts2012 · 202 citations
15. MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetZexuan Zhong et al.2023 · 199 citations
16. Affective Demonstratives and the Division of Pragmatic Labor ↗Lecture notes in computer science · no summary yetChristopher Michael Davis, Christopher E. Potts2010 · 195 citations
17. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetJon Saad-Falcon et al.2024 · 191 citations
18. Crowdsourcing and language studies: the new generation of linguistic data ↗Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk · no summary yetRobert Munro et al.2010 · 179 citations
19. Recursive Neural Networks Can Learn Logical Semantics ↗Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality · no summary yetSamuel R. Bowman, Christopher Potts, Christopher D. Manning2015 · 167 citations
20. The Life and Death of Discourse Entities: Identifying Singleton MentionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Marta Recasens, Marie-Catherine de Marneffe, Christopher Potts2013 · 166 citations
21. The syntax and semantics of As-parentheticals ↗Natural Language & Linguistic Theory · no summary yetChristopher E. Potts2002 · 159 citations
22. Colors in Context: A Pragmatic Neural Model for Grounded Language UnderstandingTransactions of the Association for Computational Linguistics (TACL)Will Monroe, Robert X.D. Hawkins, Noah D. Goodman, et al.2017 · 156 citations
23. The Pragmatic Values of Evidential Sentences ↗Proceedings from Semantics and Linguistic Theory · no summary yetChristopher Michael Davis, Christopher E. Potts, Margaret Speas2007 · 154 citations
24. Causal Abstractions of Neural Networks ↗arXiv:2106.02997 · no summary yetAtticus Geiger et al.2021 · 151 citations
25. A computational approach to politeness with application to social factorsAnnual Meeting of the Association for Computational Linguistics (ACL)Cristian Danescu-Niculescu-Mizil, Moritz Sudhof, Dan Jurafsky, et al.2013 · 141 citations

See all 270 works by Christopher E. Potts →

🤝 Co-authors here

12 of 41 co-authors with a page, the most papers together first.

• Christopher D. Manning ×5
• Noah D. Goodman ×5
• Atticus Geiger ×4
• Dan Jurafsky ×4
• Karel D'Oosterlinck ×4
• Marie-Catherine de Marneffe ×4
• Matei Zaharia ×4
• Omar Khattab ×4
• Reuben Cohn-Gordon ×3
• Adam Vogel ×2
• Andrew Ng ×2
• Chris Develder ×2

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Conference on Empirical Methods in Natural Language Processing (EMNLP) ×16: EMNLP 2025, EMNLP 2024, EMNLP 2019, EMNLP 2018, EMNLP 2015, EMNLP 2013
• Annual Meeting of the Association for Computational Linguistics (ACL) ×11: ACL 2024 ×2, ACL 2013 ×2, ACL 2011, ACL 2010
• Oxford University Press eBooks ×8
• Proceedings from Semantics and Linguistic Theory ×8
• Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) ×7
• Stanford Digital Repository ×6
• Transactions of the Association for Computational Linguistics (TACL) ×5: Transactions of the Association for Computational Linguistics (TACL) 2025, Transactions of the Association for Computational Linguistics (TACL) 2021, Transactions of the Association for Computational Linguistics (TACL) 2017
• Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) ×4: NAACL 2022, NAACL 2018, NAACL 2013 ×2
• Findings of the Association for Computational Linguistics: EMNLP 2025 ×4
• Lecture notes in computer science ×4
• neural information processing systems ×4
• Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track ×3

🔗 Cited by

Papers of our library cite their works 11,943 times (of the 149,439 papers whose bibliographies we read); 1,666 citing papers with a page here →.

Updated 30 October 2026

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