A multi-dimensional behavioral scoring system using LLM judges evaluates agentic forecast processes and closes the loop with RL penalties, yielding an 11.5% MAPE reduction in offline backtests on 2017-2025 data.
AlpacaFarm: A simulation framework for methods that learn from human feedback,
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Multi-Dimensional Behavioral Evaluation of Agentic Stock Prediction Systems Using Large Language Model Judges with Closed-Loop Reinforcement Learning Feedback
A multi-dimensional behavioral scoring system using LLM judges evaluates agentic forecast processes and closes the loop with RL penalties, yielding an 11.5% MAPE reduction in offline backtests on 2017-2025 data.