New Framework Addresses Commitment Failures in Personalized AI Systems

A new paper introduces Contract-Bounded Evidence Activation (CBEA) with Lexicographic Commitment Validation (LCV) to address failures in personalized language systems. The framework targets issues that occur after recall, when systems commit to noisy hints, drop rare evidence, or ignore infeasibility. CBEA activates bounded evidence sets using typed coverage, tail witnesses, and consequence debt, while LCV validates commitments before generating text. Across 360 test cases and three backends, CBEA+LCV achieved zero failures within validator scope at 0.49–0.60 availability, compared to 0.003–0.092 for baselines. A shadow oracle showed CBEA+LCV recalls 0.012 of uncompiled facts versus 0 for raw systems. The paper is available on arXiv.