Patronizing and Condescending Language Detection in English and Mandarin
arXiv cs.AIen
arXiv:2610.31808v1 Announce Type: new Abstract: Patronizing and condescending language (PCL) is a form of harmful language that belittles and assumes pity for vulnerable groups, reinforcing negative societal stereotypes. However, unlike overt hate speech, it is often difficult to detect, even for human judges. This paper proposes a system for the automated detection of PCL. Our first approach uses static word embeddings and a convolutional neural network for classification, while our second approach uses pre-trained BERT embeddings fine-tuned for the PCL task. Our second approach was considerably more successful, and achieved an F1 score of 0.528 over the development set.
This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.
Read the full story at arXiv cs.AI- Verktyg
- Forskning
Related AI news
- HSBC launches AI tool for corporate banking clientsTech in Asia · October 26, 2026
- A look at Toyota's robotics expansion, including its Walden spinoff and a $6.4B annual plan to deploy 400K factory robots, as it competes with Tesla and China (Financial Times)Techmeme · October 26, 2026
- Evidence-Grounded SLM Behavioral Prediction Architecture for Future Assistance UsearXiv cs.AI · October 26, 2026
- Tradeoff-Aware Territory Design: A Multi-Objective Decision System for Enterprise Customer-to-Seller AllocationarXiv cs.AI · October 26, 2026
- Phronix: The Capability-Centric Learning Paradigm for AgentsarXiv cs.AI · October 26, 2026
- PaperFormalizer: Author-in-the-Loop Autoformalization of Research Papers in LeanarXiv cs.AI · October 26, 2026