AI RESEARCH
Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems
arXiv CS.AI
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ArXi:2606.02755v1 Announce Type: cross Large language model (LLM) applications are increasingly expected to satisfy deterministic institutional requirements while relying on probabilistic generative components. This mismatch makes ordinary post-hoc benchmarking insufficient for systems that must be safe, reliable, auditable, and economically useful. This paper contributes an evaluation-protocol extension for operational LLM systems grounded in acceptance-test-driven development, safety engineering, and business-centric validation.