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Jack Lu

Hey! Iโ€™m a CS PhD candidate in the CILVR lab at NYU Courant, advised by Mengye Ren and supported by the NSERC PGS-D. Previously, I did my undergrad in CS + Math atย UWaterloo.

I study reasoning [1, 2, 3, 4] and adaptation [5, 6] in LLMs and embodied agents, as well as world models [7, 8] that agents can learn and plan in. Iโ€™m currently a visiting researcher at Meta working on recursive self-improvement, and this summer I worked on reasoning VLAs and world models at NVIDIA. Before these, I did research and engineering for autonomous driving and ML for health at NVIDIA, Waabi/Uber-ATG, IBM, and DarwinAI, working with Raquel Urtasun, Sanja Fidler, and Alexander Wong.

Iโ€™m happy to discuss collaboration, mentorship, and research in general. You can email me for a virtual or in-person chat. My office is at 60 5th Ave, New York.

news

Sep 2026 Started as a visiting researcher at Meta, working on recursive self-improvement!
Sep 2026 The Surprising Effectiveness of Deleting Weights in LLM Post-Training is accepted by NeurIPS 2026, and Solaris is accepted as a NeurIPS 2026 spotlight. See ya in ๐Ÿ‡ฆ๐Ÿ‡บ
Jul 2026 HyperThink: Text-to-Parameter Hypernetworks for Efficient Reasoning is accepted by COLM 2026. See ya in ๐ŸŒ‰
May 2026 Arrived at NVIDIA Santa Clara to work on VLA and world models. 10/10 โ˜€๏ธ, 0/10 walkability.
May 2026 The Surprising Effectiveness of Deleting Weights in LLM Post-Training is accepted by the ICML 2026 Workshop on Foundations of Deep Generative Models.
May 2026 Context Tuning for In-Context Optimization is accepted by ICML 2026. See ya in ๐Ÿ‡ฐ๐Ÿ‡ท
Jan 2026 When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers is accepted by the ICLR 2026 Workshop on AI with Recursive Self-Improvement and featured by the NYU Center for Data Science.
Jan 2026 SkillFactory: Self-Distillation For Learning Cognitive Behaviors is accepted by ICLR 2026. See ya in ๐Ÿ‡ง๐Ÿ‡ท
Jul 2024 ProCreate, Donโ€™t Reproduce! Propulsive Energy Diffusion for Creative Generation is accepted by ECCV 2024. See ya in ๐Ÿ‡ฎ๐Ÿ‡น
Apr 2024 Awarded the NSERC PGS-D Scholarship to support my PhD at NYU.
Jan 2024 SceneControl: Diffusion for Controllable Traffic Scene Generation is accepted by ICRA 2024.
Sep 2023 Started my PhD in Computer Science at NYU, advised by Mengye Ren.

publications

  1. Preprint
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    TacitVLA: Reasoning Vision-Language-Action Models Without Reasoning Latency
    Under review, 2026
  2. NeurIPS
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    The Surprising Effectiveness of Deleting Weights in LLM Post-Training
    Conference on Neural Information Processing Systems (NeurIPS); also ICML Workshop on Foundations of Deep Generative Models, 2026
  3. COLM
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    HyperThink: Text-to-Parameter Hypernetworks for Efficient Reasoning
    Conference on Language Modeling (COLM), 2026
  4. ICLRW
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    When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers
    Jack Lu*, Ryan Teehan*, Jinran Jin, and Mengye Ren
    ICLR 2026 Workshop on AI with Recursive Self-Improvement, 2026
  5. ICML
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    Context Tuning for In-Context Optimization
    Jack Lu, Ryan Teehan, Zhenbang Yang, and Mengye Ren
    International Conference on Machine Learning (ICML), 2026
  6. NeurIPS
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    Solaris: Building a Multiplayer Video World Model in Minecraft
    Conference on Neural Information Processing Systems (NeurIPS), Spotlight, 2026
  7. ICLR
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    SkillFactory: Self-Distillation For Learning Cognitive Behaviors
    International Conference on Learning Representations (ICLR), 2026
  8. ECCV
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    ProCreate, Donโ€™t Reproduce! Propulsive Energy Diffusion for Creative Generation
    Jack Lu, Ryan Teehan, and Mengye Ren
    European Conference on Computer Vision (ECCV), 2024
  9. ICRA
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    SceneControl: Diffusion for Controllable Traffic Scene Generation
    IEEE International Conference on Robotics and Automation (ICRA), 2024
  10. Frontiers
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    Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression From Chest CT Images
    Frontiers in Artificial Intelligence, 2021