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Xiangpeng Wei

Xiangpeng Wei has 3 papers in our library, in 2023–2025, most of them on Reasoning, Language models & pretraining, Multilingual & cross-lingual NLP; often with Chengyi Wang, Jiaze Chen, TianTian Fan.

3 papers in our library · 2023–2025

OpenAlex · h-index 10 · 39 works · 301 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 868 times in our library · ⭐ Paper Stars ranking: #6124

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

🏛️Chinese Academy of SciencesBeijing · China2019–2025 · 13 paperscurrent🔬Institute of Information EngineeringBeijing · China2019–2025 · 12 paperscurrent🎓University of Chinese Academy of SciencesBeijing · China2018–2021 · 11 papers🏢Alibaba DAMO AcademyHangzhou · China2022–2023 · 5 papers🏢Alibaba GroupHangzhou · China2022–2023 · 5 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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksLanguage models & pretraining · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20252 papers20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. PolyLM: An Open Source Polyglot Large Language Model (2023 · 103 citations)
    Most open LLMs are trained mainly on English, so they handle many widely spoken languages poorly. Open multilingual instruction data and a shared multilingual evaluation suite are also missing. Researchers at Alibaba's DAMO Academy tackle all three gaps. They pre-train PolyLM from scratch in two sizes, 1.7B and 13B…
  2. VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks (2025 · 68 citations)
    Most RL work on long chain-of-thought reasoning uses critic-free methods such as GRPO and DAPO. These skip the value model and estimate advantages from group rewards. ByteDance Seed's VAPO argues that a learned value model has more potential, because it gives per-token credit assignment and lower-variance estimates…
  3. Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning (2025 · 62 citations)
    Seed1.5-Thinking is a reasoning model from ByteDance Seed. It works through an extended chain of thought before giving its answer. The authors identify three factors behind strong reasoning models: training data, a stable RL algorithm and scalable RL infrastructure.

 Co-authors here

12 of 20 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 868 times (of the 149,439 papers whose bibliographies we read); 275 citing papers with a page here →.

Updated

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