5 citations · 10 across the 7 of their papers we have counts for
7 papers
HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining
Juncheng Ma, Jianxin Bi, Yufan Deng +19
Embodied foundation models are expected to benefit from data scaling like large language models, but face a much tighter data bottleneck. Teleoperated real-robot trajectories remai…
Simulus: Combining Improvements in Sample-Efficient World Model Agents
Lior Cohen, Kaixin Wang, Bingyi Kang +2
World models (WMs) represent the frontier of sample-efficient reinforcement learning, but their complexity leaves many promising improvements unrealized due to the significant expe…
Classification Done Right for Vision-Language Pre-Training
Zilong Huang, Qinghao Ye, Bingyi Kang +2
We introduce SuperClass, a super simple classification method for vision-language pre-training on image-text data. Unlike its contrastive counterpart CLIP who contrast with a text…
DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
Yang Yue, Yulin Wang, Bingyi Kang +5
MLLMs have demonstrated remarkable comprehension and reasoning capabilities with complex language and visual data. These advances have spurred the vision of establishing a generali…
How Far is Video Generation from World Model: A Physical Law Perspective
Bingyi Kang, Yang Yue, Rui Lu +5
OpenAI's Sora highlights the potential of video generation for developing world models that adhere to fundamental physical laws. However, the ability of video generation models to…
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang +1
Motivated by the success of Transformers when applied to sequences of discrete symbols, token-based world models (TBWMs) were recently proposed as sample-efficient methods. In TBWM…
Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
Yang Yue, Rui Lu, Bingyi Kang +2
The divergence of the Q-value estimation has been a prominent issue in offline RL, where the agent has no access to real dynamics. Traditional beliefs attribute this instability to…