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Fine-tuning LLMs with a data-driven pipeline that incorporates real user queries and a new augmentation method (AugFC) dramatically improves function calling performance in online financial QA systems.
LLM agents can learn to solve complex, long-horizon tasks much more effectively by using themselves as post-hoc critics to refine Q-values through hindsight reasoning.
