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SearchEyes trains search agents in simulated worlds
Published on July 8, 2026, the summary presents SearchEyes, an approach that uses a typed knowledge graph as the basis for a simulated search world to train multimodal agents.
Published on July 8, 2026, the material describes SearchEyes, which uses a typed knowledge graph to build a simulated search world and train multimodal agents. The article addresses a disconnect among training data, search environments, and reward signals in multi-hop reasoning.
The approach connects the structure of the search world to agents’ training signals. To learn about the full methods and findings, consult the original article and verify details that are not included in this summary.
Original source: SearchEyes treina agentes multimodais de busca em mundos simulados