Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

11-2025

Abstract

Recent breakthroughs in generative Artificial Intelligence (AI) have ignited a revolutionary wave across information retrieval and recommender systems. This workshop serves as a premier interdisciplinary platform to explore how generative models, particularly Large Language Models (LLMs) and Large Multimodal Models (LMMs), are transforming multimodal search and recommendation paradigms [3, 6, 9, 10, 12-14]. We aim to convene researchers and practitioners to discuss innovative architectures, methodologies, and evaluation strategies spanning generative document retrieval [5, 8] generative image retrieval [ 7, 16], grounded answer generation [17], generative recommendation [2, 4, 11], and related tasks involving multiple modalities [1,15]. The workshop will facilitate discussions on improving algorithms, generating personalized content, evolving user-system interactions, enhancing trustworthiness, and refining evaluation methodologies for these cutting-edge systems. This timely workshop seeks to identify promising research directions, address key challenges, and foster collaborations towards the development of next-generation intelligent systems.

Keywords

Multimodal Large Language Models, Generative AI, MultimodalSearch, Multimodal Recommendation

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

CIKM '25: Proceedings of the 34th ACM International Conference on Information and Knowledge Management, Seoul, Korea, November 10-14

First Page

6890

Last Page

6893

Identifier

10.1145/3746252.3761597

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3746252.3761597

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