Self-evolving visual agents learn tool use from unlabeled images using margin reward.

The Marvo framework pairs a question-generating challenger with a reinforcement-learning solver, using the solver's performance gap with and without tools to create an adaptive training curriculum.

Big Tech
Wenxi Yang · Yuzhong Zhao · Baochang Zhang · Yunfan Liu · Qixiang Ye

UCAS · Microsoft Research Asia · Beihang University

Research Digest··2 min read
The authors propose Marvo, a two-agent framework that learns tool invocation for visual agents from unlabeled images.

Marvo is a two-agent system.

Why this paper

From Microsoft Research Asia and 2 others

In one line

A margin reward based on the solver's performance difference with and without tools enables visual agents to learn tool invocation from unlabeled images.

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