no code implementations • 19 Dec 2023 • Xiaodan Zhang, Sandeep Vemulapalli, Nabasmita Talukdar, Sumyeong Ahn, Jiankun Wang, Han Meng, Sardar Mehtab Bin Murtaza, Aakash Ajay Dave, Dmitry Leshchiner, Dimitri F. Joseph, Martin Witteveen-Lane, Dave Chesla, Jiayu Zhou, Bin Chen
This study assesses the ability of state-of-the-art large language models (LLMs) including GPT-3. 5, GPT-4, Falcon, and LLaMA 2 to identify patients with mild cognitive impairment (MCI) from discharge summaries and examines instances where the models' responses were misaligned with their reasoning.
no code implementations • 23 Jul 2023 • Rui Meng, Fangzhou Zhu, Xiaodong Xu, Liang Jin, Bizhu Wang, Bingxuan Xu, Han Meng, Ping Zhang
Physical-Layer Authentication (PLA) has been recently believed as an endogenous-secure and energy-efficient technique to recognize IoT terminals.
1 code implementation • 25 Oct 2022 • Han Meng, Xiaosong He, Zexing Chen, Feng Zhou
Some Natural Language Generation (NLG) tasks require both faithfulness and diversity.
no code implementations • 10 Jun 2022 • Han Meng, Yuexing Peng, Wei Xiang, Xu Pang, Wenbo Wang
In this paper, a two-stream semantic feature fusion model, termed Multi-faceted Graph Attention Network (MF-GAT), is proposed to greatly improve the accuracy in the low SNR region of the heterogeneous radar network.
no code implementations • 15 Apr 2022 • Han Meng, Yuexing Peng, Wenbo Wang, Peng Cheng, Yonghui Li, Wei Xiang
This paper proposes a knowledge-and-data-driven graph neural network-based collaboration learning model for reliable aircraft recognition in a heterogeneous radar network.