57 citations · 218 across the 37 of their papers we have counts for
43 papers
A-MAR: Agent-based Multimodal Art Retrieval for Fine-Grained Artwork Understanding
Shuai Wang, Hongyi Zhu, Jia-Hong Huang +6
Understanding artworks requires multi-step reasoning over visual content and cultural, historical, and stylistic context. While recent multimodal large language models show promise…
Analyzing Sustainability Messaging in Large-Scale Corporate Social Media
Ujjwal Sharma, Stevan Rudinac, Ana Mićković +2
In this work, we introduce a multimodal analysis pipeline that leverages large foundation models in vision and language to analyze corporate social media content, with a focus on s…
ArtRAG: Retrieval-Augmented Generation with Structured Context for Visual Art Understanding
Shuai Wang, Ivona Najdenkoska, Hongyi Zhu +4
Understanding visual art requires reasoning across multiple perspectives -- cultural, historical, and stylistic -- beyond mere object recognition. While recent multimodal large lan…
Multimedia and Visual Analytics in the Agentic Era
Marcel Worring, Jan Zahálka, Stef van den Elzen +2
Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have rapidly changed the playing field, and i…
TULIP: Token-length Upgraded CLIP
Ivona Najdenkoska, Mohammad Mahdi Derakhshani, Yuki M. Asano +3
We address the challenge of representing long captions in vision-language models, such as CLIP. By design these models are limited by fixed, absolute positional encodings, restrict…
Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning
Athanasios Efthymiou, Stevan Rudinac, Monika Kackovic +2
In many real-world applications, modeling both the internal structure of sets and their temporal relationships is essential for capturing complex underlying patterns. Sequential mu…