Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems
A new paper proposes an evaluation protocol for business-focused large language model (LLM) systems that integrates acceptance testing. This approach aims to bridge the gap between the probabilistic nature of LLMs and the deterministic requirements of enterprises. The proposed method translates stakeholder goals into executable contracts and release gates, adapting the test-driven development cycle to a 'red-train-green' lifecycle for LLM system improvements. AI
IMPACT Introduces a framework for more reliable and auditable LLM deployments in business settings.