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DavidSunok/README.md

Junhan Sun (孙俊涵)

I am a first-year Ph.D. student in Computer Science at Zhejiang University. My research focuses on world models, JEPA, predictive representation learning, and embodied intelligence.

I study how learned world representations can move beyond predicting action effects and directly support efficient robot control.

Personal website · INTACT · X · Email

My personal website can be found here.
我的个人主页在这里。

Selected work

  • INTACT — Isomorphic Intent-to-Action Learning for Search-Free World Models.
  • CLEAR-LeWM — Auditable evaluation protocols for LeWM-compatible latent world models.

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  1. zju3dv/INTACT-JEPA zju3dv/INTACT-JEPA Public

    INTACT: Isomorphic Intent-to-Action Learning for Search-Free World Models.

    Python 174 9

  2. CLEAR-LeWM CLEAR-LeWM Public

    An auditable and reproducible evaluation suite for LeWM-compatible latent world models, with official-compatible and difficulty-controlled protocols.

    Python 35 2

  3. G1_WholebodyVLA_SONIC_dh116s G1_WholebodyVLA_SONIC_dh116s Public

    Unitree G1 Whole-Body VLA Deployment with SONIC + DH116S Hands

    Python 7