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[QA] Realistic Evaluation of Model Merging for Compositional Generalization
Manage episode 442914788 series 3524393
This paper evaluates various model merging methods for compositional generalization in image classification, generation, and NLP, clarifying their merits, requirements, and computational costs in a shared experimental setting.
https://arxiv.org/abs//2409.18314
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
1687 episódios
Manage episode 442914788 series 3524393
This paper evaluates various model merging methods for compositional generalization in image classification, generation, and NLP, clarifying their merits, requirements, and computational costs in a shared experimental setting.
https://arxiv.org/abs//2409.18314
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
1687 episódios
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