In the news
Historical Backtesting for Scientific Question Discovery: A Protocol and Astronomy Pilot
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers formalized historical backtesting to evaluate AI systems that generate scientific research questions, testing whether generated questions were later answered in real literature.
- Why it matters
- Matters for engineers building AI systems for scientific discovery who need objective evaluation beyond subjective expert scoring or LLM-as-judge ratings.
- Watch out
- Low inter-rater agreement on outcome taxonomy even among humans suggests the evaluation framework itself needs refinement, not just the judge models.
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