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[short] ReALM: Reference Resolution As Language Modeling
LLMs are powerful for reference resolution, including non-conversational entities. This paper shows how LLMs can effectively resolve various references, outperforming existing systems and even GPT-4.
https://arxiv.org/abs//2403.20329
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
LLMs are powerful for reference resolution, including non-conversational entities. This paper shows how LLMs can effectively resolve various references, outperforming existing systems and even GPT-4.
https://arxiv.org/abs//2403.20329
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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