14 papers
Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
Guanxiong Chen, Qianjun Xia, Jiawei Peng +21
Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim process must recover…
FreeStyle: Free Control of Style-Content Dual-Reference Generation from Community LoRA Mining
Jinghong Lan, Wei Cheng, Yunuo Chen +10
Style-content dual-reference generation aims to synthesize an image that preserves the structure and semantics of a content reference while adopting the style of a separate style r…
MemoryVAM: Integrating Memory into Video Action Model for Robot Manipulation
Yuxin Jiang, Chang Yu, Yunuo Chen +4
Video-world-model policies learn action-relevant representations by predicting future observations. However, they condition on only a short observation window, which renders long-h…
Sparse2Act: Learning Action-Aligned Sparse 3D Representations for Cross-Domain Robot Manipulation
Yu Guo, Chang Yu, Siyu Ma +4
Explicit 3D representations are attractive for manipulation because they expose object shape, workspace geometry, and robot-object relations in metric coordinates. However, sparse…
TacCoRL: Integrating Tactile Feedback into VLA via Simulation
Siyu Ma, Yuqi Liang, Chang Yu +5
Vision-language-action (VLA) models provide strong visual, language, and action priors for robot manipulation, but visual observations alone often miss the local contact state requ…
Learn2Fold: Structured Origami Generation with World Model Planning
Yanjia Huang, Yunuo Chen, Ying Jiang +4
The ability to transform a flat sheet into a complex three-dimensional structure is a fundamental test of physical intelligence. Unlike cloth manipulation, origami is governed by s…