4 papers
DIAL: Decoupling Intent and Action via Latent World Modeling for End-to-End VLA
Yi Chen, Yuying Ge, Hui Zhou +3
The development of Vision-Language-Action (VLA) models has been significantly accelerated by pre-trained Vision-Language Models (VLMs). However, most existing end-to-end VLAs treat…
SldprtNet: A Large-Scale Multimodal Dataset for CAD Generation in Language-Driven 3D Design
Ruogu Li, Sikai Li, Yao Mu +1
We introduce SldprtNet, a large-scale dataset comprising over 242,000 industrial parts, designed for semantic-driven CAD modeling, geometric deep learning, and the training and fin…
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…
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.…