IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation

ArXi:2511.01014v3 Announce Type: replace Instruction-following is a fundamental ability of Large Language Models (LLMs), requiring their generated outputs to follow multiple constraints imposed in input instructions. Numerous studies have attempted to enhance this ability through preference optimization or reinforcement learning based on reward signals from LLM-as-a-Judge. However, existing evaluation models for instruction-following still possess many deficiencies, such as substantial costs and unreliable assessments.