3 papers
cs.CV2026
MTA-Agent: An Open Recipe for Multimodal Deep Search Agents
Xiangyu Peng, Can Qin, An Yan +4
Multimodal large language models (MLLMs) have demonstrated strong capabilities in visual understanding, yet they remain limited in complex, multi-step reasoning that requires deep…
cs.CV2025
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents
Rui Meng, Ziyan Jiang, Ye Liu +10
Multimodal embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering over different modalities. How…
cs.CL2025
Could AI Trace and Explain the Origins of AI-Generated Images and Text?
Hongchao Fang, Yixin Liu, Jiangshu Du +7
AI-generated content is becoming increasingly prevalent in the real world, leading to serious ethical and societal concerns. For instance, adversaries might exploit large multimoda…