2026
Targeting Misalignment: A Conflict-Aware Framework for Reward-Model-based LLM Alignment
AAAI 2026technical
Reward-model-based fine-tuning is a central paradigm in aligning Large Language Models with human preferences. However, such approaches critically rely on the assumption that proxy reward models accurately reflect intended supervision, a condition often violated due to annotation noise, bias, or lim