IF-CRITIC is a fine-grained LLM critic using checklist generation and constraint-level preference optimization that outperforms strong baselines like o4-mini in instruction-following evaluation while enabling lower-cost model optimization.
During the supervised fine-tuning, the peak learning rate is set to 5e-6 with a 10% warmup ratio and a linear scheduler
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IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation
IF-CRITIC is a fine-grained LLM critic using checklist generation and constraint-level preference optimization that outperforms strong baselines like o4-mini in instruction-following evaluation while enabling lower-cost model optimization.