From the source
Decomposing data quality into independent capability dimensions February 13, 2026 SkillRater: Untangling Capabilities in Multimodal Data Decomposing data quality into independent capability dimensions February 13, 2026 SkillRater: Untangling Capabilities in Multimodal Data Decomposing data quality into independent capability dimensions One Score Isn't Enough Data filtering methods typically assign each training sample a single quality score.
This assumes quality is one-dimensional.
It isn't.
When training requires multiple capabilities — visual understanding, OCR, STEM reasoning — a single scorer can't maximize signal for all of them simultaneously.
Quality is better understood as multidimensional, with each axis corresponding to a capability the model must acquire.
Methods like CLIP score filtering measures image-text alignment but says nothing about reasoning utility.
DataRater , a meta-learned scorer, works well for text but underperforms on multimodal data.
The reason: the capabilities we care about have near-orthogonal data requirements.
Compressing them into one scalar forces tradeoffs.
Rater Per Capability …
