Inference-Time Commitment Shaping: A Framework for Quiet Failure Mitigation in LLM Systems
Abstract
This preprint introduces Inference-Time Commitment Shaping (IFCS), a conceptual and architectural framework for regulating commitment strength in large language model outputs. The work focuses on mitigating “quiet failures,” where admissible and coherent responses mislead through overstated certainty, scope, or authority. Validation is illustrative and intended to demonstrate design correctness rather than statistical generalization.
Fields of Study & Subjects
Natural Language Processing Techniques
Topic Modeling
Adversarial Robustness in Machine Learning
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 January 2026
- Language
- EN
- Document type
- Preprint