Ensemble scoring plus task-specific criteria injection raises LLM judge accuracy to 85.8 percent on RewardBench 2, a 13.5-point gain over baseline, with small models gaining the most.
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On Cost-Effective LLM-as-a-Judge Improvement Techniques
Ensemble scoring plus task-specific criteria injection raises LLM judge accuracy to 85.8 percent on RewardBench 2, a 13.5-point gain over baseline, with small models gaining the most.