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The paper introduces generative infinite-vocabulary transformers (GIVT) that generate vector sequences with real-valued entries, proposing modifications to decoder-only transformers. GIVT shows competitive results in image generation, causal modeling, panoptic segmentation, and depth estimation.
https://arxiv.org/abs//2312.02116
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
The paper introduces generative infinite-vocabulary transformers (GIVT) that generate vector sequences with real-valued entries, proposing modifications to decoder-only transformers. GIVT shows competitive results in image generation, causal modeling, panoptic segmentation, and depth estimation.
https://arxiv.org/abs//2312.02116
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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