PeopleofSuperintelligence

Researcher

Jilin Chen

As of October 2026, Jilin Chen is a researcher at Google Research whose work spans fairness, calibration and AI safety. Earlier papers from 2021 and 2022 covered fairness-accuracy trade-offs in multi-task learning and a human-ML framework for video content reviews. In September 2023, Batch Calibration, a paper on calibration for in-context learning, appeared on arXiv with Chen as a co-author. Chen is listed as Lead for Safety in the Gemini 1.0 contributions, and later work includes contributions to the Gemini 1.5 report in March 2024 and the Gemini 2.5 report in July 2025. He also co-authored Holistic Safety and Responsibility Evaluations of Advanced AI Models, which appeared on arXiv in April 2024.

Timeline

  1. 2021

    Fairness in multi-task learning

    In 2021, he co-authors a KDD paper on fairness-accuracy trade-offs in multi-task learning.

  2. 2022

    A human-ML framework for video reviews

    A human-ML collaboration framework for improving video content reviews appears at a 2022 CIKM workshop, where he is a co-author.

  3. September 2023

    Batch calibration for in-context learning

    Batch Calibration, a paper on calibration for in-context learning, appears on arXiv in September 2023 with him as co-author.

  4. December 2023

    Safety lead for the Gemini report

    He is listed as Lead for Safety in the Gemini 1.0 contributions, and the report is submitted to arXiv in December 2023.

  5. March 2024

    Contributor to the Gemini 1.5 report

    The Gemini 1.5 report, which appears on arXiv in March 2024, counts him among its contributors.

  6. April 2024

    Holistic safety evaluations

    Holistic Safety and Responsibility Evaluations of Advanced AI Models, a paper on safety evaluation for Google DeepMind's advanced AI models, appears on arXiv in April 2024 with him among its co-authors.

  7. July 2025

    Gemini 2.5 report contributor

    The Gemini 2.5 report, which appears on arXiv in July 2025, names him among its contributors.

  8. As of October 2026

    Researcher at Google Research

    He is a researcher at Google Research, with research areas in human-computer interaction and natural language processing.

Sources and credits

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  1. Jilin Chen research.google. Checked 15 October 2026.
  2. [2309.17249] Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering arxiv.org. Checked 15 October 2026.
  3. Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 15 October 2026.
  4. [2312.11805] Gemini: A Family of Highly Capable Multimodal Models arxiv.org. Checked 15 October 2026.
  5. [2403.05530] Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arxiv.org. Checked 15 October 2026.
  6. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arxiv.org. Checked 15 October 2026.
  7. Holistic Safety and Responsibility Evaluations of Advanced AI Models arxiv.org. Checked 15 October 2026.
  8. [2404.14068] Holistic Safety and Responsibility Evaluations of Advanced AI Models arxiv.org. Checked 15 October 2026.
  9. [2507.06261] Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arxiv.org. Checked 15 October 2026.
  10. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arxiv.org. Checked 15 October 2026.
  11. Paper page - Holistic Safety and Responsibility Evaluations of Advanced AI Models huggingface.co. Checked 15 October 2026.