# NimCritic: An Action-Aware Quantification Model for Long-Horizon Manipulation Progress Prediction

- Source: arXiv cs.RO
- Published: 2026-10-26T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/tn3p5xbo1k0ejdx93sg8kll93
- Original: https://arxiv.org/abs/2610.32776

## Summary

The study proposes an action-aware quantification method that uses a vision-language model to decompose long-horizon manipulation trajectories into object-level subtasks and assign weighted action credits, and builds a training video dataset of more than 800 hours plus the LOOM benchmark, which contains 19,618 human-calibrated evaluation frames.