Self-Play Preference Optimization (SPPO): An Innovative Machine Learning Approach to Finetuning Large Language Models (LLMs) from Human/AI Feedback

Large Language Models (LLMs) have demonstrated remarkable abilities in generating human-like text, answering questions, and coding. However, they face hurdles requiring high reliability, safety, and ethical adherence. Reinforcement Learning from Human Feedback (RLHF), or Preference-based Reinforcement Learning (PbRL), emerges as a promising solution. This framework has shown significant success in fine-tuning LLMs to align with […]

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