Abstract
Multimodal data is available in many applications like e-commerce production listings, social media posts and short videos. However, existing algorithms dealing with those types of data still focus on uni-modal representation learning by vision-language alignment and cross-modal retrieval. In this workshop, we target to bring a new retrieval problem where both queries and documents are multimodal. With the popularity of vision language modeling, large language models (LLMs), retrieval augmented generation (RAG), and multimodal LLM, we see a lot of new opportunities for multimodal representation and retrieval tasks. This event will be a comprehensive half-day workshop focusing on the subject of multimodal representation and retrieval. The agenda includes keynote speeches, oral presentations, and an interactive panel discussion.
Original language | English (US) |
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Title of host publication | SIGIR 2024 - Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval |
Publisher | Association for Computing Machinery, Inc |
Pages | 3047-3050 |
Number of pages | 4 |
ISBN (Electronic) | 9798400704314 |
DOIs | |
State | Published - Jul 10 2024 |
Event | 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024 - Washington, United States Duration: Jul 14 2024 → Jul 18 2024 |
Publication series
Name | SIGIR 2024 - Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval |
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Conference
Conference | 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024 |
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Country/Territory | United States |
City | Washington |
Period | 07/14/24 → 07/18/24 |
Bibliographical note
Publisher Copyright:© 2024 Owner/Author.
Keywords
- large language model
- multimodal large language model
- multimodal representation
- multimodal retrieval
- vision language modeling
ASJC Scopus subject areas
- Information Systems
- Software