25 citations · 80 across the 27 of their papers we have counts for
5 papers · 1 filter
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…
VL-KGE: Vision-Language Models Meet Knowledge Graph Embeddings
Athanasios Efthymiou, Stevan Rudinac, Monika Kackovic +2
Real-world multimodal knowledge graphs (MKGs) are inherently heterogeneous, modeling entities that are associated with diverse modalities. Traditional knowledge graph embedding (KG…
SAM3-LiteText: An Anatomical Study of the SAM3 Text Encoder for Efficient Vision-Language Segmentation
Chengxi Zeng, Yuxuan Jiang, Ge Gao +6
Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ende…
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…