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Jiang Zhong

Jiang Zhong has 2 papers in our library, in 2026, most of them on Reasoning; often with Junnan Zhu, Kaiwen Wei, Ymyang.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 7 · 57 works · 186 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #12046

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

🎓Chongqing UniversityChongqing · China2007–2026 · 19 paperscurrent🎓Jiangxi University of Science and TechnologyGanzhou · China2024–2026 · 2 paperscurrent🎓Zhejiang University of TechnologyHangzhou · China2010–2025 · 6 papers🎓Dalian Jiaotong UniversityDalian · China2019–2022 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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 9The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workHealth Information Management · 1 workHealth Professions · 1 workInformation Systems · 1 workLanguage and Linguistics · 1 workPsychology · 1 workSocial Psychology · 1 work

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation (2026)
    Generative recommenders produce semantic item IDs one step at a time. This left-to-right training tends to anchor them on the most recent interactions and miss longer-range user intent. To counter this, the authors introduce Masked History Learning (MHL), which changes how decoder-only generative models are trained.…
  2. MentalSeek-Dx: Towards Progressive Hypothetico-Deductive Reasoning for Real-world Psychiatric Diagnosis (2026)
    The paper tackles automated psychiatric diagnosis with LLMs. Existing evaluation data are mostly social-media posts or synthetic stories with coarse labels, so they say little about real clinical use. The authors build MentalDx Bench from 712 de-identified electronic health records collected at partner hospitals.…

 Co-authors here

8 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.

Updated

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