Zobrazeno 1 - 10
of 610
pro vyhledávání: '"ZHANG Xiaokun"'
Autor:
Lu, Junyu, Xu, Bo, Zhang, Xiaokun, Wang, Hongbo, Zhu, Haohao, Zhang, Dongyu, Yang, Liang, Lin, Hongfei
This paper has been accepted in the NeurIPS 2024 D & B Track. Harmful memes have proliferated on the Chinese Internet, while research on detecting Chinese harmful memes significantly lags behind due to the absence of reliable datasets and effective d
Externí odkaz:
http://arxiv.org/abs/2410.02378
Textual personality detection aims to identify personality traits by analyzing user-generated content. To achieve this effectively, it is essential to thoroughly examine user-generated content from various perspectives. However, previous studies have
Externí odkaz:
http://arxiv.org/abs/2408.08551
News recommendation emerges as a primary means for users to access content of interest from the vast amount of news. The title clickbait extensively exists in news domain and increases the difficulty for news recommendation to offer satisfactory serv
Externí odkaz:
http://arxiv.org/abs/2408.08538
Autor:
Zhong, Yuan, Wang, Xiaochen, Wang, Jiaqi, Zhang, Xiaokun, Wang, Yaqing, Huai, Mengdi, Xiao, Cao, Ma, Fenglong
Synthesizing electronic health records (EHR) data has become a preferred strategy to address data scarcity, improve data quality, and model fairness in healthcare. However, existing approaches for EHR data generation predominantly rely on state-of-th
Externí odkaz:
http://arxiv.org/abs/2406.13942
Current methods of toxic language detection (TLD) typically rely on specific tokens to conduct decisions, which makes them suffer from lexical bias, leading to inferior performance and generalization. Lexical bias has both "useful" and "misleading" i
Externí odkaz:
http://arxiv.org/abs/2406.00983
Autor:
Zhu, Haohao, Zhang, Xiaokun, Lu, Junyu, Wu, Youlin, Bai, Zewen, Min, Changrong, Yang, Liang, Xu, Bo, Zhang, Dongyu, Lin, Hongfei
Textual personality detection aims to identify personality characteristics by analyzing user-generated content toward social media platforms. Numerous psychological literature highlighted that personality encompasses both long-term stable traits and
Externí odkaz:
http://arxiv.org/abs/2404.15067
Sequential recommendation is dedicated to offering items of interest for users based on their history behaviors. The attribute-opinion pairs, expressed by users in their reviews for items, provide the potentials to capture user preferences and item c
Externí odkaz:
http://arxiv.org/abs/2404.12975
Session-based recommendation aims to predict intents of anonymous users based on their limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence patterns reflected by item IDs, and fine-grained preferences represented
Externí odkaz:
http://arxiv.org/abs/2404.12969
The session-based recommendation (SBR) garners increasing attention due to its ability to predict anonymous user intents within limited interactions. Emerging efforts incorporate various kinds of side information into their methods for enhancing task
Externí odkaz:
http://arxiv.org/abs/2402.17129
Session-based recommendation intends to predict next purchased items based on anonymous behavior sequences. Numerous economic studies have revealed that item price is a key factor influencing user purchase decisions. Unfortunately, existing methods f
Externí odkaz:
http://arxiv.org/abs/2311.01125