LLM Reasoning for Subjective Tasks: Failure Modes, Mitigation, and Dynamic Reasoning Routing
Recommendation systems thrive on personalization, where “correctness” is rarely a binary truth but a matter of subjective human preference. As Large Language Models (LLMs) are deployed as autonomous verifiers of safety and quality guidelines, they face a distinctive challenge: context-aware preference alignment. Recent...
Jun-Cheng Dong, Ding Tong, Ishan Gupta et al.
· Proceedings of the 20th ACM... · 0 citations