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Yao Dou

Yao Dou has 2 papers in our library, in 2022–2023, most of them on Language models & pretraining, Evaluation & benchmarks; often with David Heineman, Maxwell Forbes, Mounica Maddela.

2 papers in our library · 2022–2023

OpenAlex · ORCID · h-index 10 · 20 works · 581 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 149 citations in our library · 2 more in our library without a page yet · ⭐ Paper Star rank #4398

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

🎓Georgia Institute of TechnologyAtlanta · United States2022–2025 · 12 paperscurrent🎓Northwestern Polytechnical UniversityXi'an · China2014–2017 · 5 papers🎓Carnegie Mellon UniversityPittsburgh · United States2023–2024 · 2 papers🎓Chengdu PolytechnicChengdu · China2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4 Artificial Intelligence · 2 works Arts and Humanities · 2 works Computer Science · 2 works Language and Linguistics · 2 works

🧭 Topics 2 Language models & pretraining · 1 work Evaluation & benchmarks · 1 work

 Works by year

2020s

20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text (2022 · 152 citations)
    Recent work suggested that ordinary crowd workers can no longer reliably tell GPT-3 output from human writing.
  2. LENS: A Learnable Evaluation Metric for Text Simplification (2023 · 103 citations)
    Automatic scoring of text simplification is unreliable. SARI rewards n-gram overlap with references, so it penalizes valid rewordings. BERTScore barely punishes outputs that copy the input or invent content while reusing its words. The authors build the first supervised metric for the task, LENS, by fine-tuning a…

All works

4 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. Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine TextYao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, et al.Annual Meeting of the Association for… · 152 citations
  2. LENS: A Learnable Evaluation Metric for Text SimplificationMounica Maddela, Yao Dou, David Heineman, et al.Annual Meeting of the Association for… · 103 citations
  3. Improving Large-scale Paraphrase Acquisition and Generation (original ↗)Yao Dou, Chao Jiang, Wei Xu2022 · Proceedings of the 2022 Conference on Empirical… · 18 citations · no summary yet
  4. Automatic and Human-AI Interactive Text Generation (with a focus on Text Simplification and Revision) (original ↗)Yao Dou et al.2024 · Proceedings of the 62nd Annual Meeting of the… · 3 citations · no summary yet

 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 149 times (of the 141,840 papers whose bibliographies we read); 10 citing papers with a page here →.

Updated

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