ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback

Large Multimodal Models (LMMs) excel at comprehending human instructions and demonstrate remarkable results across a broad spectrum of tasks. Reinforcement Learning from Human Feedback (RLHF) and AI Feedback (RLAIF) further refine LLMs by aligning them with specific preferences. These methods primar...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Ju-Seung Byun, Chun, Jiyun, Kil, Jihyung, Perrault, Andrew
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Datasets Effectiveness Feedback Machine learning Reasoning Sentences Teachers
Online-Zugang:	Volltext
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