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Yuyan Zhou

Yuyan Zhou has 4 papers in our library, in 2026, most of them on Language models & pretraining, Reasoning, Text generation; often with Hande Dong, Hong Wang, Jianqing Zhang.

4 papers in our library · 2026

OpenAlex · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 8 times in our library · ⭐ Paper Stars ranking: #11242

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

🎓Hong Kong University of Science and TechnologyHong Kong · China2026 · 1 papercurrent🏢TencentShenzhen · China2026 · 1 papercurrent

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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksComputer Science Applications · 1 workInformation Systems · 1 workComputer Vision and Pattern Recognition · 1 work

🧭 Topics 4Research subjects and languages the work is about.Reasoning · 2 worksLanguage models & pretraining · 2 worksCode & programming languages · 1 workText generation · 1 work

 Works by year

2020s

20264 papers

 Papers

The most cited first (OpenAlex and our library).

  1. ReCreate: Reasoning and Creating Domain Agents Driven by Experience (2026 · 8 citations)
    Most practical LLM agents still depend on scaffolds that people write by hand: prompts, workflows, tools, and memory.
  2. GAPO: Robust Advantage Estimation for Real-World Code LLMs (2026 · 1 citation)
    Group-relative RL methods such as GRPO and DAPO are popular for post-training code LLMs because they need no critic.
  3. Diffusion with Truncated Blocks: Fast and High-Quality Text Generation using Truncated Block Generation (2026)
    The paper examines a weakness of diffusion-based large language models (dLLMs), which produce text by repeatedly filling in masked positions rather than writing left to right.
  4. LEPO: Latent Reasoning Policy Optimization for Large Language Models (2026)
    Latent reasoning lets LLMs think with continuous representations, such as probability-weighted vocabulary embeddings, instead of committing to one token per step.

 Co-authors here

12 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 8 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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