EvalPlanner trains LLM judges to separate planning from execution via iterative DPO on synthetic chains of thought, reaching 93.9 on RewardBench with only 22K synthetic preference pairs.
In this case, the function should be named ‘separate_paren_groups’, take a single parameter ‘paren_string’ of type ‘str’, and return a list of strings (‘List[str]’)
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Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
EvalPlanner trains LLM judges to separate planning from execution via iterative DPO on synthetic chains of thought, reaching 93.9 on RewardBench with only 22K synthetic preference pairs.