# VICTR improves robot task success using demonstration progress

> A research team reports that VICTR raised success on unseen real-world manipulation tasks to 23.8%, up from 6.2% for a fine-tuned baseline.

Oossa · 2026-11-09 · https://oossa.com/en/victr-improves-robot-task-success-using-demonstration-progress

Researchers introduce VICTR, a method that helps vision-language-action robots choose useful parts of a demonstration while carrying out a task. Instead of retrieving examples based only on visual similarity, it estimates how far the robot has progressed relative to a reference video, then supplies demonstration chunks from the matching stage to a π0.5 policy.

On unseen, out-of-domain real-world manipulation tasks, the team reports a 23.8% success rate, compared with 6.2% for a fine-tuned π0.5 baseline. The paper also reports that task progress rose from 28.9% to 55.5%; it does not establish how the method performs in broader deployment.

## The facts

- VICTR uses a progress estimator conditioned on a reference demonstration, language instruction and current observation.
- Reported success: 23.8% for VICTR versus 6.2% for the fine-tuned π0.5 baseline.

## Why it matters

For robotics researchers, VICTR suggests that matching demonstrations by task progress may help robots handle unfamiliar manipulation tasks; performance beyond the reported tests remains unknown.

## Sources & references

1. [VICTR: Value-Informed In-Context Learning for Vision-Language-Action Models](https://arxiv.org/abs/2611.08698) – arXiv cs.RO, 2026-11-09

Last updated: 2026-11-09