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Jiaqi Guo

Jiaqi Guo has 2 papers in our library, in 2021, most of them on Language models & pretraining, Question answering, Text generation; often with Jian-Guang Lou, Bei Chen, Dongmei Zhang.

2 papers in our library · 2021

OpenAlex · ORCID · h-index 24 · 56 works · 3,258 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 416 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5086

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

🎓Nankai UniversityTianjin · China2023–2025 · 6 paperscurrent🎓University of Science and Technology of ChinaHefei · China2023–2025 · 2 paperscurrent🎓China Jiliang UniversityHangzhou · China2025 · 1 papercurrent🏢State Grid Corporation of ChinaBeijing · China2025 · 1 papercurrent🏢State Grid Shanxi Electric Power CompanyTaiyuan · China2025 · 1 papercurrent🎓Xi'an Jiaotong UniversityXi'an · China2016–2023 · 32 papers🏢Microsoft Research AsiaBeijing · China2021–2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 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.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksComputer Networks and Communications · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workQuestion answering · 1 workText generation · 1 work

 Works by year

2020s

20212 papers

 Papers

The most cited first (OpenAlex and our library).

  1. TAPEX: Table Pre-training via Learning a Neural SQL Executor (2021 · 255 citations)
    Pre-training language models on tables is hard because large, clean table corpora are scarce. Web-crawled table–text pairs are noisy, and template-based synthesis is costly and repetitive. TAPEX avoids this problem by training a model to act like a SQL engine. The authors automatically sample executable SQL queries…
  2. HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation (2021 · 108 citations)
    Most table reasoning research assumes flat tables. Real statistical and scientific tables, however, often have multi-level headers, unmarked totals and proportions, and implicit links between entities. HiTab is a cross-domain English benchmark built to test question answering (QA) and table-to-text generation (NLG)…

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. Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetJiaqi Guo et al.2019 · 557 citations
  2. TAPEX: Table Pre-training via Learning a Neural SQL ExecutorarXiv:2107.07653Qian Liu, Bei Chen, Jiaqi Guo, et al.2021 · 255 citations
  3. HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language GenerationarXiv:2108.06712Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, et al.2021 · 108 citations
  4. HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhoujun Cheng et al.2022 · 61 citations

 Co-authors here

12 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 416 times (of the 149,439 papers whose bibliographies we read); 68 citing papers with a page here →.

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