1 citations · 1 across the 5 of their papers we have counts for
8 papers
Schema: Discovering Unknown Environments via Agentic Program Induction
Guanning Zeng, Jiani Wang, Wenjie Ma +8
Learning to complete tasks in unfamiliar environments with unknown rules remains a key challenge for LLM agents. Current LLM agents often record their discoveries in prose, which m…
Playful Agentic Robot Learning
Junyi Zhang, Jiaxin Ge, Hanjun Yoo +17
Current agentic robot systems can write executable Code-as-Policy programs, observe feedback, and revise behavior across multiple attempts, but they remain largely task-driven: reu…
Vision-as-Inverse-Graphics Agent via Interleaved Multimodal Reasoning
Shaofeng Yin, Jiaxin Ge, Zora Zhiruo Wang +6
Vision-as-inverse-graphics, the concept of reconstructing images into editable programs, remains challenging for Vision-Language Models (VLMs), which inherently lack fine-grained s…
Learning to Construct Knowledge through Sparse Reference Selection with Reinforcement Learning
Shao-An Yin
The rapid expansion of scientific literature makes it increasingly difficult to acquire new knowledge, particularly in specialized domains where reasoning is complex, full-text acc…
VisualMimic: Visual Humanoid Loco-Manipulation via Motion Tracking and Generation
Shaofeng Yin, Yanjie Ze, Hong-Xing Yu +2
Humanoid loco-manipulation in unstructured environments demands tight integration of egocentric perception and whole-body control. However, existing approaches either depend on ext…
RLVR-World: Training World Models with Reinforcement Learning
Jialong Wu, Shaofeng Yin, Ningya Feng +1
World models predict state transitions in response to actions and are increasingly developed across diverse modalities. However, standard training objectives such as maximum likeli…
Trajectory World Models for Heterogeneous Environments
Shaofeng Yin, Jialong Wu, Siqiao Huang +4
Heterogeneity in sensors and actuators across environments poses a significant challenge to building large-scale pre-trained world models on top of this low-dimensional sensor info…
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Jialong Wu, Shaofeng Yin, Ningya Feng +4
World models empower model-based agents to interactively explore, reason, and plan within imagined environments for real-world decision-making. However, the high demand for interac…