
Sign up to save your podcasts
Or


This study evaluates model merging at scale, revealing insights on expert model quality, size, and merging methods, ultimately enhancing generalization and performance in large-scale applications.
https://arxiv.org/abs//2410.03617
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
This study evaluates model merging at scale, revealing insights on expert model quality, size, and merging methods, ultimately enhancing generalization and performance in large-scale applications.
https://arxiv.org/abs//2410.03617
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

970 Listeners

1,967 Listeners

436 Listeners

111,948 Listeners

10,182 Listeners

5,530 Listeners

195 Listeners

52 Listeners

101 Listeners

491 Listeners