Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 31·5 min read
Fidelity Is Not Enough: Dispatch-Level Instrumentation for Agentic Datasheet Extraction
TL;DR
A new approach to agentic datasheet extraction reveals that fidelity alone is insufficient for reliable model evaluation. By implementing dispatch-level instrumentation, the researchers identified silent failures in model outputs that passed fidelity checks.
✦ Why It Matters
Implement dispatch-level instrumentation to improve the reliability of your model evaluations today.
Key Takeaways
- Implement logging for tool calls in model evaluations.
- Use failure-attribution classifiers to identify extraction issues.
- Incorporate physical measurement verification for claims.
- Recognize the limitations of fidelity as a sole evaluation metric.
How It Works
The researchers developed a logging system that records each tool call during the extraction process. This allows for the identification of silent failures, where models produce incorrect outputs without triggering fidelity checks.
The silent-failure detector operates independently of the extracted values, focusing solely on the tools used.