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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…
Towards Patronizing and Condescending Language in Chinese Videos: A Multimodal Dataset and Detector
Hongbo Wang, Junyu Lu, Yan Han +3
Patronizing and Condescending Language (PCL) is a form of discriminatory toxic speech targeting vulnerable groups, threatening both online and offline safety. While toxic speech re…
Integrating Multi-view Analysis: Multi-view Mixture-of-Expert for Textual Personality Detection
Haohao Zhu, Xiaokun Zhang, Junyu Lu +2
Textual personality detection aims to identify personality traits by analyzing user-generated content. To achieve this effectively, it is essential to thoroughly examine user-gener…
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…
IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models
Qiyao Wang, Jianguo Huang, Shule Lu +4
The rapid development of Large Language Models (LLMs) in vertical domains, including intellectual property (IP), lacks a specific evaluation benchmark for assessing their understan…
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…