Towards a Reliable and Practical Eval Pipeline
Quick summary
arXiv:2609.00805v1 Announce Type: new Abstract: LLM-based software systems increasingly require effective "evals" as quality gates in the development lifecycle. However, existing work typically addresses individual aspects of eval reliability rather than the full set of practical requirements. We present an end-to-end eval pipeline that combines eval checklist creation, with learned aggregation for checklist responses, to improve agreement across LLM judges and accuracy against human judgments. The framework additionally pro- vides self-consistency, explanations, and prediction uncertainty, an
Key takeaways
- arXiv:2609.00805v1 Announce Type: new Abstract: LLM-based software systems increasingly require effective "evals" as quality gates in the development lifecycle.
- However, existing work typically addresses individual aspects of eval reliability rather than the full set of practical requirements.
- We present an end-to-end eval pipeline that combines eval checklist creation, with learned aggregation for checklist responses, to improve agreement across LLM judges and accuracy against human judgments.
Why it matters
The importance of “Towards a Reliable and Practical Eval Pipeline” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.
Member comments