MTA-Agent generates 21K verified multi-hop vision-language QA trajectories via tool-augmented evidence synthesis, allowing a 32B open model to outperform GPT-5 and Gemini variants on complex multimodal benchmarks while increasing reasoning steps.
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MTA-Agent: An Open Recipe for Multimodal Deep Search Agents
MTA-Agent generates 21K verified multi-hop vision-language QA trajectories via tool-augmented evidence synthesis, allowing a 32B open model to outperform GPT-5 and Gemini variants on complex multimodal benchmarks while increasing reasoning steps.