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Chain-of-thought prompting enhances reasoning in large language models, particularly for math and logic tasks, but shows limited benefits for other tasks, suggesting a need for new computational paradigms.
https://arxiv.org/abs//2409.12183
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
By Igor Melnyk5
33 ratings
Chain-of-thought prompting enhances reasoning in large language models, particularly for math and logic tasks, but shows limited benefits for other tasks, suggesting a need for new computational paradigms.
https://arxiv.org/abs//2409.12183
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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