Jiaqi Gao¹, Kangfeng Zheng^1,*, Xiujuan Wang², Chunhua Wu¹, Bin Wu²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 251-270, 2024, DOI:10.32604/cmc.2024.055560 - 15 October 2024

Abstract User identity linkage (UIL) refers to identifying user accounts belonging to the same identity across different social media platforms. Most of the current research is based on text analysis, which fails to fully explore the rich image resources generated by users, and the existing attempts touch on the multimodal domain, but still face the challenge of semantic differences between text and images. Given this, we investigate the UIL task across different social media platforms based on multimodal user-generated contents (UGCs). We innovatively introduce the efficient user identity linkage via aligned multi-modal features and temporal correlation… More >

Zheyi Chen^1,, Liuchang Xu^1,, Hongting Zheng¹, Luyao Chen¹, Amr Tolba^2,3, Liang Zhao⁴, Keping Yu^5,*, Hailin Feng^1,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 1753-1808, 2024, DOI:10.32604/cmc.2024.052618 - 15 August 2024

Abstract Since the 1950s, when the Turing Test was introduced, there has been notable progress in machine language intelligence. Language modeling, crucial for AI development, has evolved from statistical to neural models over the last two decades. Recently, transformer-based Pre-trained Language Models (PLM) have excelled in Natural Language Processing (NLP) tasks by leveraging large-scale training corpora. Increasing the scale of these models enhances performance significantly, introducing abilities like context learning that smaller models lack. The advancement in Large Language Models, exemplified by the development of ChatGPT, has made significant impacts both academically and industrially, capturing widespread… More >