3 papers
cs.AI2026
PReD: An LLM-based Foundation Multimodal Model for Electromagnetic Perception, Recognition, and Decision
Zehua Han, Jing Xiao, Yiqi Duan +13
Multimodal Large Language Models have demonstrated powerful cross-modal understanding and reasoning capabilities in general domains. However, in the electromagnetic (EM) domain, th…
cs.CV2026
MERLIN: Building Low-SNR Robust Multimodal LLMs for Electromagnetic Signals
Junyu Shen, Zhendong She, Chenghanyu Zhang +13
The paradigm of Multimodal Large Language Models (MLLMs) offers a promising blueprint for advancing the electromagnetic (EM) domain. However, prevailing approaches often deviate fr…
cs.CL2024
Asynchronous and Segmented Bidirectional Encoding for NMT
Jingpu Yang, Zehua Han, Mengyu Xiang +3
With the rapid advancement of Neural Machine Translation (NMT), enhancing translation efficiency and quality has become a focal point of research. Despite the commendable performan…