1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AI2026
Thinker-WM: A Unified World Model with Shared Multimodal Representations for Embodied Intelligence
Thinker Team, Peng Gao, Jichao Jiao +8
World models have emerged as a promising paradigm for embodied AI, yet existing systems often remain fragmented in the modalities they model and the functions they support. In part…
cs.CV2026
Thinker: A vision-language foundation model for embodied intelligence
Baiyu Pan, Daqin Luo, Junpeng Yang +4
When large vision-language models are applied to the field of robotics, they encounter problems that are simple for humans yet error-prone for models. Such issues include confusion…
cs.LG2024★ 1 cited
AutoM3L: An Automated Multimodal Machine Learning Framework with Large Language Models
Daqin Luo, Chengjian Feng, Yuxuan Nong +1
Automated Machine Learning (AutoML) offers a promising approach to streamline the training of machine learning models. However, existing AutoML frameworks are often limited to unim…