7 papers
From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation
Yibin Liu, Yaxing Lyu, Daqi Gao +5
Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video MLLMs, trained primarily under a Supervi…
Mixture of Horizons in Action Chunking
Dong Jing, Gang Wang, Jiaqi Liu +7
Vision-language-action (VLA) models have shown remarkable capabilities in robotic manipulation, but their performance is sensitive to the used during…
Rethinking Intermediate Representation for VLM-based Robot Manipulation
Weiliang Tang, Jialin Gao, Jia-Hui Pan +6
Vision-Language Model (VLM) is an important component to enable robust robot manipulation. Yet, using it to translate human instructions into an action-resolvable intermediate repr…
COS3D: Collaborative Open-Vocabulary 3D Segmentation
Runsong Zhu, Ka-Hei Hui, Zhengzhe Liu +5
Open-vocabulary 3D segmentation is a fundamental yet challenging task, requiring a mutual understanding of both segmentation and language. However, existing Gaussian-splatting-base…
Moto: Latent Motion Token as the Bridging Language for Learning Robot Manipulation from Videos
Yi Chen, Yuying Ge, Weiliang Tang +5
Recent developments in Large Language Models pre-trained on extensive corpora have shown significant success in various natural language processing tasks with minimal fine-tuning.…
Incentivizing Multimodal Reasoning in Large Models for Direct Robot Manipulation
Weiliang Tang, Dong Jing, Jia-Hui Pan +5
Recent Large Multimodal Models have demonstrated remarkable reasoning capabilities, especially in solving complex mathematical problems and realizing accurate spatial perception. O…