Reinforcement Learning as a fine-tuning paradigm

Reinforcement Learning should be better seen as a “fine-tuning” paradigm that can add capabilities to general-purpose foundation models, rather than a paradigm that can bootstrap intelligence from scratch.

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The AiEdge+: How to fine-tune Large Language Models with Intermediary models

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Machine Learning Paradigms - Introduction to Machine Learning

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Complete Guide On Fine-Tuning LLMs using RLHF

Distilling step-by-step: Outperforming larger language models with

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LoRA — Intuitively and Exhaustively Explained

The uneasy relationship between deep learning and (classical

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9 Reinforcement Learning Real-Life Applications

Frontiers Self-Net: Lifelong Learning via Continual Self-Modeling