Jekyll2026-01-27T07:25:06+00:00https://lucys0.github.io/feed.xmlLucy X. ShiThe personal page of Lucy Xiaoyang Shi. Lucy Xiaoyang Shilucyshi@stanford.eduCtrl-World: A Controllable Generative World Model for Robot Manipulation2026-01-01T00:00:00+00:002026-01-01T00:00:00+00:00https://lucys0.github.io/example/research/ctrlA controllable world model that can evaluate and improve VLA policies.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduHi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models2025-02-26T00:00:00+00:002025-02-26T00:00:00+00:00https://lucys0.github.io/example/research/hi

We are teaching robots to listen and think harder.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduYell At Your Robot: Improving On-the-Fly from Language Corrections2024-03-20T00:00:00+00:002024-03-20T00:00:00+00:00https://lucys0.github.io/example/research/yayYAY Robot leverages verbal corrections to enable on-the-fly adaptation and continuous policy improvement on complex long-horizon tasks.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduCross-Episodic Curriculum for Transformer Agents2023-10-14T00:00:00+00:002023-10-14T00:00:00+00:00https://lucys0.github.io/example/research/cecCEC enhances Transformer agents’ learning efficiency and generalization by structuring cross-episodic experiences in-context.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduWaypoint-Based Imitation Learning for Robotic Manipulation2023-08-04T00:00:00+00:002023-08-04T00:00:00+00:00https://lucys0.github.io/example/research/aweWe propose an automatic method for extracting waypoints from demonstrations for performant imitation learning.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduSkill-based Model-based Reinforcement Learning2022-07-04T00:00:00+00:002022-07-04T00:00:00+00:00https://lucys0.github.io/example/research/skimoWe devise a method that enables model-based RL on long-horizon, sparse-reward tasks, allowing us to learn with 5x less samples.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduTharsians2020-10-01T00:00:00+00:002020-10-01T00:00:00+00:00https://lucys0.github.io/example/mars/tharsiansWith my two brilliant friends Jessica Yuan and Albert Sun we published a paper exploring a Mars city state of 1 million people. We were the only undergraduate team to win the finalist (10 /176) and present at the 23rd Annual International Mars Society Convention. The paper was also later included as a chapter in the book, Mars City States: New Societies for a New World, published in 2021.

Looking back, it was a wonderful summer of reading and thinking intensively to paint a coherent picture of the future. It gave me an epiphany that a myriad of things in the world are profoundly connected, and AI will be an important driving force behind many things I care about — like an interplanetary humanity, robotics, and universal education.

]]>Lucy Xiaoyang Shilucyshi@stanford.eduRpl2020-01-01T00:00:00+00:002020-01-01T00:00:00+00:00https://lucys0.github.io/example/rpl/rplIn parallel to the physics stuff I was also an avionics engineer at the USC Rocket Propulsion Lab (think: build brains for rockets). We are the first student group to successfully launch and recover an entirely student-designed rocket (Traveler IV) past the Karman line, the recognized boundary of space at 100 km (328,084 ft)! There were so many difficulties to overcome, but launching a rocket in desert is one of my best college memories! I love this group of people — they are ambitious, hungry for getting things to work, and incredibly caring. They also taught me if you care about something deeply enough, the reality becomes negotiable.

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