
Sign up to save your podcasts
Or


This paper introduces StreamingLLM, an efficient framework that allows large language models to generalize to infinite sequence length in streaming applications without fine-tuning. It addresses challenges related to memory consumption and text length, and achieves stable and efficient language modeling.
https://arxiv.org/abs//2309.17453
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 paper introduces StreamingLLM, an efficient framework that allows large language models to generalize to infinite sequence length in streaming applications without fine-tuning. It addresses challenges related to memory consumption and text length, and achieves stable and efficient language modeling.
https://arxiv.org/abs//2309.17453
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

956 Listeners

1,976 Listeners

438 Listeners

112,847 Listeners

10,064 Listeners

5,532 Listeners

213 Listeners

51 Listeners

98 Listeners

473 Listeners