8 citations · 11 across the 4 of their papers we have counts for
6 papers
DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine
Haozhe Lou, Runyi Yang, Wanqi Zhong +10
Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plastic object whose behavior chang…
RIFAR: Reliability-Informed and Forgetting-Aware Replay for Continual Robot Learning with World-Action Models
Zirui Song, Tu Lin, Zirong Song +11
Genuine embodied agency requires robots to turn continuous real-world experience into lasting, transferable skills. This demands continual learning that integrates new capabilities…
LayerRoute: Action-Conditioned Mixture-of-Layers Routing for Vision-Language-Action Policies
Zheng Lu, Zirong Song, Haoran Liao +11
Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hierarchical visual-semantic repr…
Planning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners
Zirong Song, Zheng Lu, Mingqi Gao +11
Current benchmarks for embodied vision-language planning inadvertently favor linguistic next-token prediction over physically grounded next-state reasoning. This rewards models tha…
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
Yunxin Li, Shenyuan Jiang, Baotian Hu +5
Recent advancements in Multimodal Large Language Models (MLLMs) underscore the significance of scalable models and data to boost performance, yet this often incurs substantial comp…
A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question Answering
Yunxin Li, Longyue Wang, Baotian Hu +5
The emergence of multimodal large models (MLMs) has significantly advanced the field of visual understanding, offering remarkable capabilities in the realm of visual question answe…