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[short] Greed is All You Need: An Evaluation of Tokenizer Inference Methods
Study compares tokenization methods for NLP models, finding greedy inference effective and SaGe superior for morphological alignment.
https://arxiv.org/abs//2403.01289
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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By Igor Melnyk
5
33 ratings
Study compares tokenization methods for NLP models, finding greedy inference effective and SaGe superior for morphological alignment.
https://arxiv.org/abs//2403.01289
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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