31 citations · 63 across the 16 of their papers we have counts for
8 papers · 1 filter
Towards Comprehensive Detection of Chinese Harmful Memes
Junyu Lu, Bo Xu, Xiaokun Zhang +5
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 significant…
PclGPT: A Large Language Model for Patronizing and Condescending Language Detection
Hongbo Wang, Mingda Li, Junyu Lu +5
Disclaimer: Samples in this paper may be harmful and cause discomfort! Patronizing and condescending language (PCL) is a form of speech directed at vulnerable groups. As an essenti…
Don't Click the Bait: Title Debiasing News Recommendation via Cross-Field Contrastive Learning
Yijie Shu, Xiaokun Zhang, Youlin Wu +3
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 incre…
Take its Essence, Discard its Dross! Debiasing for Toxic Language Detection via Counterfactual Causal Effect
Junyu Lu, Bo Xu, Xiaokun Zhang +4
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…
FineRec:Exploring Fine-grained Sequential Recommendation
Xiaokun Zhang, Bo Xu, Youlin Wu +3
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 fo…
Disentangling ID and Modality Effects for Session-based Recommendation
Xiaokun Zhang, Bo Xu, Zhaochun Ren +3
Session-based recommendation aims to predict intents of anonymous users based on their limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence pa…
Enhancing Textual Personality Detection toward Social Media: Integrating Long-term and Short-term Perspectives
Haohao Zhu, Xiaokun Zhang, Junyu Lu +7
Textual personality detection aims to identify personality characteristics by analyzing user-generated content on social media platforms. Extensive psychological literature highlig…
Side Information-Driven Session-based Recommendation: A Survey
Xiaokun Zhang, Bo Xu, Chenliang Li +3
The session-based recommendation (SBR) garners increasing attention due to its ability to predict anonymous user intents within limited interactions. Emerging efforts incorporate v…