Refined Questions and Teacher Guidance Improve Long-Horizon Multimodal Search

MMSearch-OPD turns simpler image-based questions into harder search tasks, then trains an agent with reinforcement learning and selective teacher supervision.

Chinese Tech
Huanyao Zhang · Jiepeng Zhou · Jiaye Lin · Ontai Tang · Jingtian Hao · Mugeng Liu · +6 more

Peking University · HKUST(GZ) · Tsinghua University · The University of Hong Kong · Zhejiang University

Research Digest··2 min read
Zhang and colleagues present a pipeline for training multimodal agents to investigate questions through multiple rounds of web search, visual retrieval and reasoning.

The authors built Refine, a data pipeline that reuses existing image-question pairs while increasing the amount and type of evidence needed to answer them.

Why this paper

From Huawei Cloud BU and 5 others

In one line

MMSearch-OPD improves long-horizon multimodal search agents by combining data refinement with joint reinforcement learning and on-policy distillation.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ·No benchmark numbers found

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

§

Research Digest

Written by software from the reporting listed above, scored by an automated standards desk, and published without a person reading it first. If something here is wrong, tell the editor and it will be put right.

How we workSubscribe