5 papers
LARA: Latent Action Representation Alignment for Vision-Language-Action Models
Mengya Liu, Baoxiong Jia, Jiangyong Huang +2
Visual-language action (VLA) models enable robots to predict actions directly from observations and language instructions, but their performance depends on large-scale, high-qualit…
3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
Xiongkun Linghu, Jiangyong Huang, Baoxiong Jia +1
Reinforcement Learning with Verifiable Rewards ( RLVR ) has emerged as a transformative paradigm for enhancing the reasoning capabilities of Large Language Models ( LLMs), yet its…
ARFlow: Human Action-Reaction Flow Matching with Physical Guidance
Wentao Jiang, Jingya Wang, Kaiyang Ji +3
Human action-reaction synthesis, a fundamental challenge in modeling causal human interactions, plays a critical role in applications ranging from virtual reality to social robotic…
Multi-modal Situated Reasoning in 3D Scenes
Xiongkun Linghu, Jiangyong Huang, Xuesong Niu +3
Situation awareness is essential for understanding and reasoning about 3D scenes in embodied AI agents. However, existing datasets and benchmarks for situated understanding are lim…
F-HOI: Toward Fine-grained Semantic-Aligned 3D Human-Object Interactions
Jie Yang, Xuesong Niu, Nan Jiang +2
Existing 3D human object interaction (HOI) datasets and models simply align global descriptions with the long HOI sequence, while lacking a detailed understanding of intermediate s…