pith:LTWHYP5B
Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents
On-policy data evolution from agent rollouts boosts multimodal deep search performance from 24.9% to 39% on average.
arxiv:2605.10832 v2 · 2026-05-11 · cs.CL
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Claims
Across 8 multimodal deep search benchmarks, ODE improves the Qwen3-VL-8B agent from 24.9% to 39.0% on average, surpassing Gemini-2.5 Pro in standard agent-workflow setting (37.9%). At 30B, ODE raises the average score from 30.6% to 41.5%.
That rollouts from the current policy produce training data that accurately identifies and fills the precise capability gaps without introducing self-reinforcing biases or training instability.
A new image-bank harness and closed-loop on-policy data evolution method raises multimodal agent performance on visual search benchmarks from 24.9% to 39.0% for an 8B model and from 30.6% to 41.5% for a 30B model.
Receipt and verification
| First computed | 2026-06-08T01:04:07.308478Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5cec7c3fa156c1763f97956b1445a8f42f43b136365004d76ce88b6d7247b0c5
Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/LTWHYP5BK3AXMP4XSVVRIRNI6Q \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 5cec7c3fa156c1763f97956b1445a8f42f43b136365004d76ce88b6d7247b0c5
Canonical record JSON
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