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Jianzhe Ma

Jianzhe Ma has 2 papers in our library, in 2026, most of them on Question answering, Multilingual & cross-lingual NLP, Reasoning; often with Qin Jin, Wenxuan Wang, Liang Zhang.

2 papers in our library · 2026

OpenAlex · h-index 0 · 2 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10929

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

🎓Renmin University of ChinaBeijing · China2026 · 2 paperscurrent

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 9The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArts and Humanities · 1 workMathematics · 1 workArtificial Intelligence · 1 workComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 workApplied Mathematics · 1 workComputational Theory and Mathematics · 1 workGeometry and Topology · 1 work

🧭 Topics 4Research subjects and languages the work is about.Reasoning · 1 workMultilingual & cross-lingual NLP · 1 workQuestion answering · 1 workVision & language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering (2026 · 2 citations)
    Benchmarks for chart understanding are almost entirely in English, so little is known about how large vision-language models (LVLMs) handle charts in other languages.
  2. A Survey of Deep Learning for Geometry Problem Solving (2026 · 1 citation)
    This survey maps how deep learning is used to solve geometry problems. The task is a long-standing test of machine mathematical reasoning and a natural multimodal benchmark, because solving a problem means reading a diagram, reasoning logically and computing numbers. The authors began from classic papers, ran one…

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. POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Yichen Xu, Liangyu Chen, Liang Zhang, et al.2026 · 2 citations
  2. A Survey of Deep Learning for Geometry Problem SolvingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianzhe Ma, Wenxuan Wang, Qin Jin2026 · 1 citation
  3. A Survey of Large Models in Sports ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetYichen Xu 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 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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