Digital content is nowadays available from multiple, heterogeneous sources across a wide range of sensing modalities. Learning from multimodal sources offers the unprecedented possibility of capturing ...

In this tutorial, we build a RAG-Anything workflow and use it to explore how multimodal retrieval works across text, tables, equations, and images. We start by preparing the Colab environment, ...

Generative AI tools have made multimodal content creation accessible to teachers, sharply reducing the time and expertise needed to produce it—a shift with significant pedagogical implications. This ...

This repository provides a structured, community-maintained survey of multimodal models, covering the full evolutionary arc from early fusion methods to today's natively-trained omni-models. We ...

CaM-HG: Causal-Enhanced MoE and Hypergraphs Network for Incomplete Multimodal Emotion Recognition in Conversations ACL Finding 2026 N/A QA-MoE: Towards a Continuous Reliability Spectrum with ...