arxiv
PublishedOctober 21, 2026 at 4:00 AM
EDMA: Entropy-Driven Multimodal Answering
Publisher summary· verbatim
arXiv:2610.27120v1 Announce Type: new Abstract: Multimodal question answering (MMQA) is based on integrating heterogeneous data sources, selectively leveraging relevant modalities, and ignoring distractors. Existing approaches based on Multimodal Large Language Models (MLLMs) improve performance by
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivAn AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response4harxivNavalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training4harxivLarge language model and reinforcement learning based autonomous construction and progress updates4harxivMedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring4hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗