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RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models

RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models

FromDeep Papers


RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models

FromDeep Papers

ratings:
Length:
44 minutes
Released:
Oct 18, 2023
Format:
Podcast episode

Description

We discuss RankVicuna, the first fully open-source LLM capable of performing high-quality listwise reranking in a zero-shot setting. While researchers have successfully applied LLMs such as ChatGPT to reranking in an information retrieval context, such work has mostly been built on proprietary models hidden behind opaque API endpoints. This approach yields experimental results that are not reproducible and non-deterministic, threatening the veracity of outcomes that build on such shaky foundations. RankVicuna provides access to a fully open-source LLM and associated code infrastructure capable of performing high-quality reranking.Find the transcript and more here: https://arize.com/blog/rankvicuna-paper-reading/To learn more about ML observability, join the Arize AI Slack community or get the latest on our LinkedIn and Twitter.
Released:
Oct 18, 2023
Format:
Podcast episode

Titles in the series (23)

Deep Papers is a podcast series featuring deep dives on today’s seminal AI papers and research. Hosted by AI Pub creator Brian Burns and Arize AI founders Jason Lopatecki and Aparna Dhinakaran, each episode profiles the people and techniques behind cutting-edge breakthroughs in machine learning.