1st Workshop on Multimodal Search and Recommendations (CIKM MMSR '24)

With the advent of multimodal LLMs and release of open-source multimodal models, the potential for multimodal search and recommendations has significantly increased. Multimodal systems offer a next-gen customer experience by creating a shared embedding space for text, images, audio, etc. These advancements enable more accurate, personalized recommendations, enhancing user satisfaction and engagement. This workshop on Multimodal Search and Recommendations explores the latest advancements, challenges, and applications of multimodal search and recommendations.

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Publication Details

Published
2024-10-20
DOI
https://doi.org/10.1145/3627673.3679082
Citations
1
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.35
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article

1st Workshop on Multimodal Search and Recommendations (CIKM MMSR '24)

Surya Kallumadi, Tracy Holloway King, Aditya Chichani, Andrei Lopatenko
1 citations
Natural Language Processing Techniques
0.35
article

1st Workshop on Multimodal Search and Recommendations (CIKM MMSR '24)

Surya Kallumadi, Tracy Holloway King, Aditya Chichani, Andrei Lopatenko
article en
1 citations

Abstract

With the advent of multimodal LLMs and release of open-source multimodal models, the potential for multimodal search and recommendations has significantly increased. Multimodal systems offer a next-gen customer experience by creating a shared embedding space for text, images, audio, etc. These advancements enable more accurate, personalized recommendations, enhancing user satisfaction and engagement. This workshop on Multimodal Search and Recommendations explores the latest advancements, challenges, and applications of multimodal search and recommendations.

Adobe Systems (United States) (US), Walmart (United States) (US), Independent Sector (US)
Openalex Percentile: Top 32%
Natural Language Processing Techniques
0.35
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