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Lost in the Middle: How Language Models Use Long Contexts
Language models struggle to effectively use longer context in tasks such as multi-document question answering and key-value retrieval. Performance is highest when relevant information is at the beginning or end of the context, and decreases as the context grows longer.
https://arxiv.org/abs//2307.03172
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
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
Language models struggle to effectively use longer context in tasks such as multi-document question answering and key-value retrieval. Performance is highest when relevant information is at the beginning or end of the context, and decreases as the context grows longer.
https://arxiv.org/abs//2307.03172
YouTube: https://www.youtube.com/@ArxivPapers
PODCASTS:
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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