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This paper presents a framework for self-rewarding reasoning in LLMs, enabling autonomous error detection and correction, enhancing performance without external feedback, demonstrated through experiments with Llama-3 and Qwen-2.5.
https://arxiv.org/abs//2502.19613
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
5
33 ratings
This paper presents a framework for self-rewarding reasoning in LLMs, enabling autonomous error detection and correction, enhancing performance without external feedback, demonstrated through experiments with Llama-3 and Qwen-2.5.
https://arxiv.org/abs//2502.19613
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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