🧑‍🔬 Jinyi Hu

🏛️ Affiliations

🎓Hong Kong Polytechnic UniversityHong Kong · China2025–2026 · 4 paperscurrent🎓Tsinghua UniversityBeijing · China2020–2024 · 13 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems (2024 · 456 citations)
   Frontier models now score near the top on older math benchmarks like GSM8K and MATH. With prompting, GPT-4 reaches 97.0% and 84.3% on them. Existing physics and multimodal test sets also tend to be easy, narrow in scope, or text-only. To give harder targets, the authors built OlympiadBench, a bilingual…
2. Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages (2023 · 43 citations)
   Most large multimodal systems for image understanding and image generation work well only in English. Other languages lack the huge image-text collections such training needs: BLIP-2 used over 100M pairs, and Stable Diffusion used over 2B. The authors propose MPM, a training paradigm that uses a multilingual LLM as a…
3. Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from Experience (2025 · 19 citations)
   Seed-Prover 1.5 (ByteDance Seed AI4Math) asks whether formal theorem proving in Lean can match the progress of natural-language LLM proving without large compute costs.

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific ProblemsAnnual Meeting of the Association for Computational Linguistics (ACL)Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.2024 · 456 citations
2. RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback ↗arXiv:2312.00849 · no summary yetTianyu Yu et al.2023 · 217 citations
3. Large Multilingual Models Pivot Zero-Shot Multimodal Learning across LanguagesarXiv:2308.12038Jinyi Hu, Yuan Yao, Chongyi Wang, et al.2023 · 43 citations
4. Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from ExperiencearXiv:2512.17260Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.2025 · 19 citations

🤝 Co-authors here

12 of 22 co-authors with a page, the most papers together first.

• Xu Han ×2
• Chaoqun He
• Chongyi Wang
• Jiangjie Chen
• Jie Liu
• Junhao Shen
• Lei Qi
• Mingxuan Wang
• Qianyu Chen
• Renjie Luo
• Shan Wang
• Shengding Hu

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2024

🔗 Cited by

Papers of our library cite their works 569 times (of the 149,439 papers whose bibliographies we read); 141 citing papers with a page here →.

Updated 31 October 2026

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