Neos turns visual evidence into better follow-up search decisions

The framework jointly trains a search policy and visual evidence interface to support long, multimodal research tasks.

Chinese Tech
Ekko He · Jack Hong · Shilin Yan · Xintong Zhang · Yujie Zhang · Wenjie Li · +5 more

Fudan University · Accio Team, Alibaba Group · Shanghai Innovation Institute

Research Digest··2 min read
He and colleagues present Neos, a multimodal search framework designed to make retrieved images actively shape later queries and tool use.

The authors synthesized training tasks that require intermediate visual evidence to determine subsequent search steps.

Why this paper

From Accio Team, Alibaba Group and 2 others

In one line

Neos learns to interleave search and visual reasoning, achieving leading performance on multimodal deep search benchmarks.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ✓Reports numbers on named benchmarks

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