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OneSearch-VL grounds multimodal research agents in an evidence graph

huggingface.co by Hongyu Li et al. Editor score 8/10

OneSearch-VL uses a visually grounded evidence graph to connect image and video anchors, retrieved facts and answer operations, with dedicated training data and benchmarks. This offers a concrete design for traceable tool use in multimodal research agents.

What: - OneSearch-VL is a multimodal research agent organized around a Visually Grounded Evidence Graph (VGEG).
Method: - VGEG supports data construction, process supervision, and operation-level evaluation; EVGR uses its annotations to supervise evidence traceability and visual grounding during RL.
Why it matters: - The paper reports OneSearch-VL-8B outperforming Qwen3-VL-8B with tool access on two new benchmarks, highlighting the value of grounding research operations in evidence.

VGEG supports data preparation and evidence-aware reward supervision for RL. Sketched from the article's own text.

Read on huggingface.co → Code · 2 stars

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