PeopleofSuperintelligence

Researcher

Shuting Pan

Shuting Pan is a researcher whose papers include DeepSeek-AI reports on large language models. They coauthored the 2024 DeepSeek-V3 report, which introduced a 671-billion-parameter mixture-of-experts model. DeepSeek-R1 and DeepSeek-V3.2 reports in 2025 described reinforcement-learning reasoning, sparse attention and tool-use training. They coauthored DeepSeek-V4's 2026 report on million-token context and, as of October 2026, are a coauthor of DeepSeek-V4.1-Flash, a report on KV-cache compression and multimodal agent tasks.

Works
6
Citations
1,968
h-index
4

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2024

    DeepSeek-V3 report

    In 2024, they coauthor the DeepSeek-V3 Technical Report, which presents a 671-billion-parameter mixture-of-experts language model with 37 billion parameters active for each token.

  2. January 2025

    DeepSeek-R1 reasoning

    In January 2025, they coauthor the DeepSeek-R1 report, which uses pure reinforcement learning to develop reasoning behaviors such as self-reflection, verification and dynamic strategy adaptation without human-labeled reasoning trajectories.

  3. December 2025

    DeepSeek-V3.2 report

    In December 2025, they coauthor the DeepSeek-V3.2 report, which introduces DeepSeek Sparse Attention, scalable reinforcement learning and an agentic task-synthesis pipeline for tool use.

  4. April 2026

    DeepSeek-V4 context

    In April 2026, they coauthor the DeepSeek-V4 report, which presents two mixture-of-experts models for one-million-token context and uses compressed attention to improve long-context efficiency.

  5. As of October 2026

    DeepSeek-V4.1-Flash report

    As of October 2026, they are a coauthor of DeepSeek-V4.1-Flash, submitted in September 2026, a report on KV-cache compression that describes a 45-trillion-token multimodal corpus and post-training for text and multimodal agent tasks.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. The United States employs an estimated 48% of people shaping AIWe estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  3. 43% of living people shaping AI work outside their country of birthWe estimate that 43% of living people shaping AI work outside their country of birth (520 of 1,198 people with known birth and employment countries).
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionWe estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Sources and credits

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  1. [2412.19437] DeepSeek-V3 Technical Report arxiv.org. Checked 20 October 2026.
  2. DeepSeek-V3 Technical Report | Cool Papers - Immersive Paper Discovery papers.cool. Checked 20 October 2026.
  3. [2501.12948] DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning arxiv.org. Checked 20 October 2026.
  4. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning - 智源社区论文 hub.baai.ac.cn. Checked 20 October 2026.
  5. [2512.02556] DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arxiv.org. Checked 20 October 2026.
  6. DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence | Cool Papers - Immersive Paper Discovery papers.cool. Checked 20 October 2026.
  7. [2609.19969] DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression arxiv.org. Checked 20 October 2026.