SearchEyes

by Frostlinx · indexed from github

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation. A typed knowledge graph unifies data synthesis (PKC), environment simulation, and RL training (HaPO) for multi-hop visual search agents. SearchEyes-27B achieves SOTA among open-source multimodal search agents on 6 benchmarks.

A typed knowledge graph serves as the unified backbone for three tightly-coupled stages: PKC question synthesis (left), a self-contained search world for agent interaction (center), and hop-anchored reward signals for policy optimization (right).

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