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Liliang Ren

Member of Technical Staff, Thinking Machines Lab

Liliang Ren is a Member of Technical Staff at Thinking Machines Lab and was previously at Microsoft Superintelligence, according to Ren's site. Ren is the first author of "Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation" (2025), which introduced the SambaY architecture used in Microsoft's Phi-4-mini-flash-reasoning model, and of Samba (2024), a hybrid state-space architecture for language modeling with unlimited context. Ren earned a PhD in computer science at the University of Illinois Urbana-Champaign, advised by ChengXiang Zhai.123

At a glance

Current role
Member of Technical Staff
Sector
Company
Education
UC San Diego, UIUC
Work listed
2
Sources cited
4
Profile reviewed

Career

Ren completed a PhD in computer science at the University of Illinois Urbana-Champaign, advised by ChengXiang Zhai, after a master's degree at the University of California San Diego. During the PhD, Ren held research internships at Microsoft Research in 2022 and at Amazon Science in 2023.1

Ren later worked at Microsoft Superintelligence and is now a Member of Technical Staff at Thinking Machines Lab.1

Research

Ren's research aims at neural architectures with greater efficiency and capacity. Samba, posted in June 2024 with Weizhu Chen as senior author, combines state-space layers with sliding-window attention for language modeling with unlimited context length. The SambaY paper, posted in July 2025, introduces a decoder-hybrid-decoder design and was released with Phi-4-mini-flash-reasoning and a training codebase.132

Ren's site notes five papers accepted at NeurIPS 2025, including SambaY and Routing Mamba, and a March 2026 paper on hyperparameter transfer for scaling training compute.1

Work and contributions

  • Phi-4-mini-flash-reasoning Open weights

    First author of the SambaY paper behind Phi-4-mini-flash-reasoning; Ren's site announces the model's July 2025 release together with the paper and its training codebase.214

  • Samba Published research

    First author of Samba, a hybrid architecture combining state-space layers with attention for efficient long-context language modeling, presented at ICLR 2025.31

Timeline

  1. Began a research internship in the Knowledge and Language Team at Microsoft Research.1
  2. Posted the Samba paper on hybrid state-space language models as first author.3
  3. Released Phi-4-mini-flash-reasoning with the SambaY paper as first author.12
  4. Had five papers accepted at NeurIPS 2025, including SambaY.1
  5. Announced a paper on stable and optimal learning-rate transfer for training compute scaling.1

Other documented roles

Roles the sources document that are not confirmed as current.

Where they work

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References

4 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026

  1. Liliang Ren — homepageLiliang Ren · Official page · accessed Oct 22, 2026
  2. Decoder-Hybrid-Decoder Architecture for Efficient Reasoning with Long Generation (arXiv 2507.06607)arXiv · Paper · published Jul 9, 2025 · accessed Oct 22, 2026
  3. Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling (arXiv 2406.07522)arXiv · Paper · published Jun 11, 2024 · accessed Oct 22, 2026
  4. microsoft/Phi-4-mini-flash-reasoning model cardMicrosoft (Hugging Face) · Model card · accessed Oct 22, 2026