PeopleofSuperintelligence

Researcher

Xuheng Lin

Xuheng Lin is an AI researcher whose DeepSeek work spans reasoning and long-context language models. DeepSeek credited him as a contributor to its V3 report in 2024 and its V3.2 report in 2025, and he coauthored the R1 report in January 2025. Nature published a DeepSeek-R1 article with Lin among its authors in September 2025; he also coauthored DeepSeek-V4, a model series with million-token contexts, in 2026. In September 2026, he contributes to DeepSeek-AI's Research & Engineering team and coauthors its V4.1-Flash report on KV-cache compression.

Now at
DeepSeek

Timeline

  1. 2024

    DeepSeek-V3 contributor credits

    In December 2024, DeepSeek credits him as a contributor to V3, its 671-billion-parameter mixture-of-experts model with 37 billion parameters active per token.

  2. January 2025

    DeepSeek-R1 and reasoning

    In January 2025, he coauthors DeepSeek-R1, whose report shows that pure reinforcement learning can incentivize reasoning in language models.

  3. September 2025

    DeepSeek-R1 in Nature

    Nature publishes its DeepSeek-R1 article in September 2025 with Lin among its authors. The study describes how reinforcement learning can incentivize reasoning in language models.

  4. December 2025

    DeepSeek-V3.2 contributor credits

    In December 2025, DeepSeek credits him as a contributor to V3.2.

  5. 2026

    DeepSeek-V4 context models

    In 2026, he coauthors DeepSeek-V4, a pair of mixture-of-experts language models that support one-million-token contexts.

  6. September 2026

    Research and engineering at DeepSeek

    In September 2026, he contributes to DeepSeek-AI's Research & Engineering team and coauthors its V4.1-Flash report on KV-cache compression.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes DeepSeek. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes DeepSeek. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  3. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staffIncludes DeepSeek. 5,000 frontier users would be 38.2% of the core labs' 13,100 reported staff. We test the estimate against 3,913 named model contributors and dated all-staff records across Google DeepMind, OpenAI and Anthropic, plus six additional frontier-grade labs.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes DeepSeek. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. DeepSeek-V3 Technical Report arxiv.org. Checked 21 October 2026.
  2. DeepSeek-V3 Technical Report arxiv.org. Checked 21 October 2026.
  3. Xuheng Lin | 500AI 500ai.org. Checked 21 October 2026.
  4. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning arxiv.org. Checked 21 October 2026.
  5. DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning nature.com. Checked 21 October 2026.
  6. DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arxiv.org. Checked 21 October 2026.
  7. DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arxiv.org. Checked 21 October 2026.
  8. DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arxiv.org. Checked 21 October 2026.