most citedFactorLLM: Factorizing Knowledge via Mixture of Experts for Large Language Models

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cs.RO2025★ 1 cited

Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain

Yulin Luo, Chun-Kai Fan, Menghang Dong +19

Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems often follow a dual-system paradigm, w…

cs.RO2025

MoLe-VLA: Dynamic Layer-skipping Vision Language Action Model via Mixture-of-Layers for Efficient Robot Manipulation

Rongyu Zhang, Menghang Dong, Yuan Zhang +6

Multimodal Large Language Models (MLLMs) excel in understanding complex language and visual data, enabling generalist robotic systems to interpret instructions and perform embodied…