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Jianghao Lin

Jianghao Lin has 2 papers in our library, in 2026, most of them on Reasoning; often with Jiachen Zhu, Rong Shan, Weinan Zhang.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 13 · 66 works · 795 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 11 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #13643

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

🎓Shanghai Jiao Tong UniversityShanghai · China2021–2026 · 58 papersEmploymentcurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksBusiness, Management and Accounting · 1 workInformation Systems · 1 workManagement Information Systems · 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. A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage (2026)
    Reasoning alignment for LLMs has mostly relied on outcome reward models (ORMs). These judge only the final answer, so an extended chain of thought receives just one coarse signal. This survey covers Process Reward Models (PRMs), which score individual steps or whole trajectories. It frames the field as a cycle…
  2. A Survey of Large Language Model-Based Search Agents (2026)
    The paper reviews LLM-based search agents. These are systems in which a language model runs the whole information-seeking process itself: it interprets the user's goal, plans queries, retrieves over several rounds, reflects on what it found, and merges evidence into an answer. Commercial tools such as OpenAI's Deep…

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. A Survey of AI Agent Protocols ↗arXiv:2504.16736 · no summary yetYingxuan Yang et al.2025 · 20 citations
  2. A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and UsageAnnual Meeting of the Association for Computational Linguistics (ACL)Congmin Zheng, Jiachen Zhu, Zhuoying Ou, et al.2026
  3. A Survey of Large Language Model-Based Search AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Yunjia Xi, Jianghao Lin, Yongzhao Xiao, et al.2026
  4. Position: Academic Conferences are Potentially Facing Denominator Gaming Caused by Fully Automated Scientific Agents ↗arXiv:2605.09915 · no summary yetRong Shan et al.2026

 Co-authors here

9 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

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