| Autor: |
Bénédict, Gabriel1 (AUTHOR) g.benedict@uva.nl, Zhang, Ruqing2 (AUTHOR) zhangruqing@ict.ac.cn, Metzler, Donald3 (AUTHOR) metzler@google.com, Yates, Andrew4 (AUTHOR) a.yates@uva.nl, Deffayet, Romain5 (AUTHOR) r.e.deffayet@uva.nl, Hager, Philipp6 (AUTHOR) p.k.hager@uva.nl, Jullien, Sami7 (AUTHOR) s.jullien@uva.nl |
| Předmět: |
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| Zdroj: |
SIGIR Forum. Dec2023, Vol. 57 Issue 2, p1-23. 23p. |
| Abstrakt: |
The first edition of the workshop on Generative Information Retrieval (Gen-IR 2023) took place in July 2023 in a hybrid fashion, co-located with the ACM SIGIR Conference 2023 in Taipei (SIGIR 2023). The aim was to bring information retrieval researchers together around the topic of generative AI that gathered attention in 2022 and 2023 with large language models and diffusion models. Given the novelty of the topic, the workshop was focused around multi-sided discussions, namely panels and poster sessions of the accepted proceedings papers. Two main research outcomes are the proceedings of the workshop1 and the potential research directions discussed in this report. Date: 27 July 2023. Website: https://coda.io/@sigir/gen-ir. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Library, Information Science & Technology Abstracts |
| Externí odkaz: |
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