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.
Authors
- Surya Kallumadi (ORCID: https://orcid.org/0000-0002-5638-0482)
- Tracy Holloway King (ORCID: https://orcid.org/0000-0002-7956-505X)
- Aditya Chichani
- Andrei Lopatenko
Institutions
- Adobe Systems (United States) (US)
- Walmart (United States) (US)
- Independent Sector (US)
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