This is a Plain English Papers summary of a research paper called AI System Learns Quality Data Selection from Just 30 Human Examples. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Overview
- New method called CritiQ for selecting high-quality training data for language models
- Uses only 30 human-annotated pairs to develop quality criteria
- Employs manager and worker agents to evolve data selection criteria
- Builds knowledge base from previous research
- Validated on code, math, and logic domains
- Shows improved performance compared to traditional methods
Plain English Explanation
Think of CritiQ as a smart quality control system for language model training data. Instead of having humans manually review thousands of examples, it learns what "good" looks like from just a few human-rated samples.
[Data selection methods](https://aimodels.fyi/papers/arxiv/...
Top comments (0)