MUSE: A Unified Agentic Harness for MLLMs 事件

MUSE: A Unified Agentic Harness for MLLMs arXiv:2606.03005v1 Announce Type: new Abstract: Despite rapid progress, multimodal large language models (MLLMs) still fail on tasks that humans solve effortlessly, such as navigating a grid maze from a screenshot or selecting the correct puzzle piece. Rather than retraining the model, we ask a complementary question: how much capability can be elicited from a frozen MLLM purely by improving the execution scaffold around it? We introduce MUSE, a multimo