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Jingwei Xiong

Jingwei Xiong has 2 papers in our library, in 2026, most of them on Language models & pretraining; often with Haixu Tang, Pin-Yu Chen, Tsung-Yi Ho.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 4 · 15 works · 67 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 11 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #12984

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

🎓University of California, DavisDavis · United States2022–2026 · 12 paperscurrent🎓National University of Defense TechnologyChangsha · China2023 · 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workHealth Informatics · 1 workLanguage and Linguistics · 1 workMedicine · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Hey, That's My Data! Token-Only Dataset Inference in Large Language Models (2026 · 1 citation)
    Owners who suspect an LLM was trained on their proprietary or copyrighted text usually need log-probabilities to test this. Many commercial APIs, however, return only greedy top-1 tokens. The authors address this token-only setting with CatShift, which uses catastrophic forgetting as an auditing signal.
  2. “Excuse me, may I say something...” CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert Collaborations (2026)
    Most LLM assistants for science are reactive: they speak only when asked. In a live research meeting, that means useful remarks may never be made. This paper presents CoLabScience, an assistant that follows biomedical team discussions as they unfold and decides on its own when to contribute and what to say.

All works

3 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. Elevating Legal LLM Responses: Harnessing Trainable Logical Structures and Semantic Knowledge with Legal Reasoning ↗Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetRujing Yao et al.2025 · 17 citations
  2. Hey, That's My Data! Token-Only Dataset Inference in Large Language ModelsFindings of the Association for Computational LinguisticsChen Xiong, Zihao Wang, Rui Zhu, et al.2026 · 1 citation
  3. “Excuse me, may I say something...” CoLabScience, A Proactive AI Assistant for Biomedical Discovery and LLM-Expert CollaborationsAnnual Meeting of the Association for Computational Linguistics (ACL)Yang Wu, Jinhong Yu, Jingwei Xiong, et al.2026

 Co-authors here

6 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 11 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated

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