Edge 377: LLM Reasoning with Reinforced Fine-Tuning
Was this email forwarded to you? Sign up here Edge 377: LLM Reasoning with Reinforced Fine-TuningA very recent LLM reasoning technique created by ByteDance research.In this Issue:
💡 ML Concept of the Day: Reinforced Fine-Tuning and LLM ReasoningIn the last installment of our series about LLM reasoning, we are going to discuss a new technique recently introduced by ByteDance. Reinforced Fine-Tuning(ReFT) looks to address some of the limitation of supervised fine tuning(SFT) approaches such as chain of thought(CoT) of reliance on reasoning training data. The core idea is to create models that can learn from multiple reasoning paths for a single questions... ![]() Continue reading this post for free, courtesy of Jesus Rodriguez.A subscription gets you:
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