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Zeqi Tan

Zeqi Tan has 2 papers in our library, in 2021–2024, most of them on Named entity recognition; often with Weiming Lu, Yongliang Shen, Guiyang Hou.

2 papers in our library · 2021–2024

OpenAlex · h-index 11 · 48 works · 671 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 139 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5068

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

🎓East China University of TechnologyNanchang · China2026 · 2 paperscurrent🎓Zhejiang UniversityHangzhou · China2021–2025 · 37 papers🎓ShanghaiTech UniversityShanghai · China2023 · 3 papers🎓National University of SingaporeSingapore · Singapore2013–2017 · 3 papers🏢Alibaba GroupHangzhou · China2023 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 9 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksBiochemistry, Genetics and Molecular Biology · 1 workMolecular Biology · 1 work

🧭 Topics 1Research subjects and languages the work is about.Named entity recognition · 1 work

 Works by year

2020s

20241 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition (2021 · 232 citations)
    The paper addresses nested named entity recognition, where entities can contain other entities. Span-based approaches handle nesting naturally, but they have four weaknesses: they enumerate many low-quality candidates, which is computationally costly; they cannot reach entities longer than the enumeration limit; they…
  2. Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization (2024 · 52 citations)
    Most LLM-based agents depend on hand-written prompts that fix task rules and behavior. They cannot improve through experience, so they struggle in dynamic multi-agent settings with hidden information. Agent-Pro tackles this by treating policy learning as gradient-free prompt optimization, with no parameter updates.

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. Locate and Label: A Two-stage Identifier for Nested Named Entity RecognitionAnnual Meeting of the Association for Computational Linguistics (ACL)Yongliang Shen, Xinyin Ma, Zeqi Tan, et al.2021 · 232 citations
  2. Parallel Instance Query Network for Named Entity Recognition ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYongliang Shen et al.2022 · 98 citations
  3. PromptNER: Prompt Locating and Typing for Named Entity Recognition ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYongliang Shen et al.2023 · 83 citations
  4. Agent-Pro: Learning to Evolve via Policy-Level Reflection and OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Ke Tang, Hai Wu, et al.2024 · 52 citations

 Co-authors here

10 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 139 times (of the 149,439 papers whose bibliographies we read); 12 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/zeqi-tan/