MMSkills Framework Enables Multimodal Skill Learning for Visual Agents

A new framework called MMSkills has been developed by researchers to represent, generate, and utilize reusable multimodal procedures for visual agents. This initiative responds to the shortcomings of current skill packages that mainly represent behavior through text or code. The authors contend that procedural knowledge for visual agents is fundamentally multimodal, necessitating the recognition of pertinent states, visual evidence interpretation, and decision-making. MMSkills addresses three key challenges: outlining the components of a multimodal skill package, creating these packages from public interaction experiences, and allowing agents to reference multimodal evidence during inference without relying heavily on image context or specific screenshots. The paper can be found on arXiv with the ID 2605.13527.