🧑‍🔬 Shuyue Guo

🏛️ Affiliations

🎓Tianjin Medical UniversityTianjin · China2023–2026 · 12 paperscurrent🏥Tianjin Medical University Cancer Institute and HospitalTianjin · China2023–2026 · 12 paperscurrent🔬Sandia National LaboratoriesAlbuquerque · United States2016–2026 · 6 papersEmployment since 2016 · R&D Material Scientist, Explosive Technologies Groupcurrent🎓Beihang UniversityBeijing · China2026 · 1 papercurrent🏛️Chinese Academy of SciencesBeijing · China2014–2020 · 11 papers🎓University of Chinese Academy of SciencesBeijing · China2014–2020 · 9 papers🔬Beijing National Laboratory for Molecular SciencesBeijing · China2016–2020 · 8 papers🔬Institute of ChemistryBeijing · China2016–2020 · 8 papers🎓Beijing University of Posts and TelecommunicationsBeijing · China2022–2025 · 3 papers🏥Institut du cancer Rosalind & Morris GoodmanMontreal · Canada2023–2024 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 15 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. CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization (2026 · 12 citations)
   Turning informal math problems into Lean 4 theorem statements often produces code that compiles but does not mean what the original problem says.
2. MdEval: Massively Multilingual Code Debugging (2026 · 12 citations)
   Most existing code-debugging benchmarks for LLMs, such as DebugBench and DebugEval, cover only one to three languages and are mostly Python-centred.
3. Scaling Laws for Code: Every Programming Language Matters (2026 · 2 citations)
   Classic scaling laws treat code as a single, language-agnostic domain. In practice, programming languages (PLs) contribute unequally during pre-training, so loss predictions for multilingual code LLMs can be inaccurate. This study runs more than 1000 pre-training experiments from scratch, costing roughly 336,000 H800…
4. V-GameGym: Visual Game Generation for Code Large Language Models (2026 · 1 citation)
   Existing code benchmarks mostly check whether generated programs compile and pass tests. They largely ignore what matters for games: whether the result is playable, looks right and behaves coherently over time. V-GameGym fills this gap with a benchmark for visual game generation in Python/Pygame. The authors mined…

🤝 Co-authors here

12 of 24 co-authors with a page, the most papers together first.

• Jian Yang ×3
• Linzheng Chai ×3
• Wei Zhang ×3
• Aishan Liu
• Bowen Zhou
• Bryan Dai
• Chenchen Zhang
• Ganqu Cui
• He Zhu
• Hualei Zhu
• Jiaheng Liu
• Jiajun Shi

Venues

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

• Findings of the Association for Computational Linguistics ×3: Findings of the Association for Computational Linguistics 2026 ×3
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026

🔗 Cited by

Papers of our library cite their works 52 times (of the 149,439 papers whose bibliographies we read); 15 citing papers with a page here →.

Updated 31 October 2026

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