A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio, et al.
This paper introduces FoMo-in-Flux, a continual multimodal pretraining benchmark with realistic compute constraints, and provides comprehensive guidance for effective continual model updates in real-world deployment scenarios.
Ying-Chao Ma, Anders Oland, Anton Ragni, et al.
This paper provides a comprehensive review of foundation models in music, covering representation, generative, and multimodal learning, and highlighting underexplored areas and future directions.
Aditya Bharat Soni, Boxuan Li, Xingyao Wang, et al.
OpenHands-Versa is a generalist agent using a minimal set of general tools—code editing/execution, web search, multimodal browsing, and file access—that outperforms specialized agents across SWE-Bench Multimodal, GAIA, and The Agent Company.
Unknown
This paper discusses the potential high-level and long-term benefits of using multimodal large language models (M-LLMs) in health care, including their ability to integrate diverse data types for improved clinical decision-making.
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This paper reviews the applications, challenges, and future outlook of multimodal large language models in healthcare, emphasizing their role in integrating diverse medical data for improved clinical decision-making.
Aurélie Pahud de Mortanges, Haozhe Luo, Shelley Zixin Shu, et al.
This paper reviews XAI for multimodal and longitudinal medical imaging data and proposes an XAI orchestrator to help clinicians synthesize data, predictions, and explanations.
Yue Fan, Xuehai He, Diji Yang, et al.
GRIT trains multimodal LLMs to generate reasoning chains interleaving text and bounding boxes, using RL with robust rewards to achieve data-efficient visual grounding.
Jy-oti Aneja, Michael Harrison, Neel Joshi, et al.
Phi-4-reasoning-vision-15B is a compact open-weight multimodal reasoning model demonstrating that careful architecture and data curation enable competitive performance with significantly less compute.
Yipeng Hu, Marc Modat, Eli Gibson, et al.
This paper introduces a weakly-supervised CNN approach for multimodal image registration that learns voxel-level transformations from anatomical labels, enabling real-time, fully-automated inference without labels.
Unknown
This paper surveys the field of embodied AI, covering fundamentals, hardware systems, and the integration of LLMs and multimodal LLMs to create world models.
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This paper provides a guide for implementing a fully local multimodal RAG system to analyze product datasheets, avoiding rate limits of paid online services.
Shengxu Xu, Hongsong Wang
MMRDoc introduces a multi-granularity multimodal RAG framework that improves long-document VQA by enhancing semantic representation and retrieval.