Title
Signal Conditioned Agents for Lightweight Perception
Description
Computer use agents are expensive and unreliable across long context windows due to the vision + language + agentic complexity, and the cost and unreliability of VLM agents compounds across long running steps. This project aims to build on top of Microsoft's OmniParser architecture and explore integration of implicit brain signals as a new source of data to augment and validate computer use agents' actions, and to make computer use agents more reliable and safe across long multi-step scenarios.
Project url
https://github.com/Thomson-Lam/brainhacks-26-proposal/tree/main
Project Leads
Thomson Lam (@Thomson-Lam)