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Data curation via joint example selection further accelerates multimodal learning
Manage episode 425855212 series 3524393
Jointly selecting batches of data improves learning in large-scale pretraining. Multimodal contrastive objectives reveal data dependencies, leading to faster training with reduced computational overhead.
https://arxiv.org/abs//2406.17711
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
1276 episodes
Manage episode 425855212 series 3524393
Jointly selecting batches of data improves learning in large-scale pretraining. Multimodal contrastive objectives reveal data dependencies, leading to faster training with reduced computational overhead.
https://arxiv.org/abs//2406.17711
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
1276 episodes
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