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Chris Piech

Chris Piech has 2 papers in our library, in 2023, most of them on Language models & pretraining, Dialogue systems; often with Allen Nie, Anaïs Tack, Ekaterina Kochmar.

2 papers in our library · 2023

OpenAlex · ORCID · Wikidata · h-index 26 · 109 works · 6,234 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,123 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #8599

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Stanford UniversityStanford · United States2012–2026 · 88 papersEducationEmployment · Assistant Professor, Computer Sciencecurrent🎓Central University of EcuadorQuito · Ecuador2023 · 2 papers🤝IMECLeuven · Belgium2023 · 2 papers🎓KU LeuvenLeuven · Belgium2023 · 2 papers🎓King's College LondonLondon · United Kingdom2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 workCognitive Neuroscience · 1 workNeuroscience · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 2Research subjects and languages the work is about.Dialogue systems · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20232 papers

 Papers

The most cited first (OpenAlex and our library).

  1. The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues (2023 · 51 citations)
    This paper reports on the first shared task that tests whether generative language models can act as AI teachers by producing the next teacher turn in a real teacher–student conversation.
  2. MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks (2023 · 41 citations)
    Large language models are increasingly used as stand-ins for people, yet aggregate accuracy scores reveal little about whether they reason like humans.

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial in a Large-Scale Online Course ↗Educational Evaluation and Policy Analysis · no summary yetDorottya Demszky et al.2023 · 128 citations
  2. The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational DialoguesWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Anaïs Tack, Ekaterina Kochmar, Zheng Yuan, et al.2023 · 51 citations
  3. MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment TasksConference on Neural Information Processing Systems (NeurIPS)Allen Nie, Yuhui Zhang, Atharva Amdekar, et al.2023 · 41 citations
  4. Machine Translation for Nko: Tools, Corpora, and Baseline Results ↗Proceedings of the Eighth Conference on Machine Translation · no summary yetMoussa Doumbouya et al.2023 · 12 citations
  5. Handwritten Code Recognition for Pen-and-Paper CS Education ↗ACM Conference on Learning @ Scale (L@S) · no summary yetMd Sazzad Islam et al.2024 · 6 citations

 Co-authors here

7 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 1,123 times (of the 149,439 papers whose bibliographies we read); 267 citing papers with a page here →.

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