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[QA] Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
Manage episode 449774697 series 3524393
The SPA framework enhances user experience by generating diverse, high-quality responses from foundation models using synthetic data and data attribution methods, improving performance in code generation and natural language tasks.
https://arxiv.org/abs//2411.06722
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
--- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/support
1701 episodes
Manage episode 449774697 series 3524393
The SPA framework enhances user experience by generating diverse, high-quality responses from foundation models using synthetic data and data attribution methods, improving performance in code generation and natural language tasks.
https://arxiv.org/abs//2411.06722
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
--- Support this podcast: https://podcasters.spotify.com/pod/show/arxiv-papers/support
1701 episodes
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