2025
QA‐LIGN: Aligning LLMs through Constitutionally Decomposed QA
EMNLP 2025
Alignment of large language models (LLMs) with principles like helpfulness, honesty, and harmlessness typically relies on scalar rewards that obscure which objectives drive the training signal. We introduce QA-LIGN, which decomposes monolithic rewards into interpretable principle-specific evaluation