activity
20202026
most citedWorld Model as a Graph: Learning Latent Landmarks for Planning

22 citations · 39 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2026

LongCat-Next: Lexicalizing Modalities as Discrete Tokens

Meituan LongCat Team, Bin Xiao, Chao Wang +86

The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…

cs.CV2025

Control Map Distribution using Map Query Bank for Online Map Generation

Ziming Liu, Leichen Wang, Ge Yang +4

Reliable autonomous driving systems require high-definition (HD) map that contains detailed map information for planning and navigation. However, pre-build HD map requires a large…

cs.RO2024

Learning Visual Parkour from Generated Images

Alan Yu, Ge Yang, Ran Choi +3

Fast and accurate physics simulation is an essential component of robot learning, where robots can explore failure scenarios that are difficult to produce in the real world and lea…

cs.LG2023

Compositional Sculpting of Iterative Generative Processes

Timur Garipov, Sebastiaan De Peuter, Ge Yang +3

High training costs of generative models and the need to fine-tune them for specific tasks have created a strong interest in model reuse and composition. A key challenge in composi…

cs.CV2023★ 9 cited

Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation

William Shen, Ge Yang, Alan Yu +3

Self-supervised and language-supervised image models contain rich knowledge of the world that is important for generalization. Many robotic tasks, however, require a detailed under…

cs.RO2023★ 1 cited

Neural Volumetric Memory for Visual Locomotion Control

Ruihan Yang, Ge Yang, Xiaolong Wang

Legged robots have the potential to expand the reach of autonomy beyond paved roads. In this work, we consider the difficult problem of locomotion on challenging terrains using a s…