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cs.CL2026
Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use
Zhixin Ma, Yutong Zhou, Yongqi Li +2
Multimodal Large Language Models (MLLMs) excel at utilizing digital APIs and increasingly serve as the "brain" of embodied AI, instructing robots to interact with the physical worl…
cs.CL2026
Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied Agents
Hanlin Wang, Chak Tou Leong, Jian Wang +1
Recent advancements in large language models (LLMs) have enabled agents to tackle complex embodied tasks through environmental interaction. However, these agents still make subopti…