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Lan-Zhe Guo

Lan-Zhe Guo has 2 papers in our library, in 2026, most of them on Evaluation & benchmarks, Reasoning; often with Ming Yang, Wei Dong, Xin Li.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 11 · 62 works · 369 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 49 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #10942

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

🎓Nanjing UniversityNanjing · China2017–2026 · 46 paperscurrent

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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputational Theory and Mathematics · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Reasoning · 1 workEvaluation & benchmarks · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. TabularMath: Understanding Math Reasoning over Tables with Large Language Models (2026 · 3 citations)
    Most math benchmarks for LLMs use plain-text word problems. Real tasks such as business intelligence or financial reports instead require multi-step arithmetic over tables that may be large, incomplete, or contradictory. Existing table benchmarks rely on manual collection, which limits their scale, and they seldom…
  2. Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling (2026)
    As LLMs turn into agents that call tools over many turns, reward models must judge entire interaction trajectories, not just single replies.

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. LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model ↗arXiv:2406.04614 · no summary yetZhi Zhou et al.2024 · 56 citations
  2. LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM ↗arXiv:2502.06572 · no summary yetZhi Zhou et al.2025 · 9 citations
  3. TabularMath: Understanding Math Reasoning over Tables with Large Language ModelsFindings of the Association for Computational LinguisticsShi-Yu Tian, Zhi Zhou, Wei Dong, et al.2026 · 3 citations
  4. Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.2026

 Co-authors here

5 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 49 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated

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