1 citations · 2 across the 8 of their papers we have counts for
9 papers
Data Pyramid for Embodied Manipulation: A Survey
Yifan Ye, Yankai Fu, Yaoxu Lv +26
Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…
Efficient-VLN: A Simple yet Strong Baseline for Efficient Vision-Language Navigation
Duo Zheng, Shijia Huang, Yanyang Li +1
While Multimodal Large Language Models (MLLMs) have demonstrated significant promise in Vision-Language Navigation (VLN), existing agents remain heavily constrained by systemic bot…
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors
Duo Zheng, Shijia Huang, Yanyang Li +1
Previous research has investigated the application of Multimodal Large Language Models (MLLMs) in understanding 3D scenes by interpreting them as videos. These approaches generally…
CLEVA: Toward Comprehensive and Contamination-Free Language Model Evaluation
Yanyang Li, Tin Long Wong, Cheung To Hung +5
Recent advances in large language models (LLMs) have shown significant promise, yet their evaluation raises concerns, particularly regarding data contamination due to the lack of a…
Video-3D LLM: Learning Position-Aware Video Representation for 3D Scene Understanding
Duo Zheng, Shijia Huang, Liwei Wang
The rapid advancement of Multimodal Large Language Models (MLLMs) has significantly impacted various multimodal tasks. However, these models face challenges in tasks that require s…
Towards Learning a Generalist Model for Embodied Navigation
Duo Zheng, Shijia Huang, Lin Zhao +2
Building a generalist agent that can interact with the world is the intriguing target of AI systems, thus spurring the research for embodied navigation, where an agent is required…