P cl GPT : A Large Language Model for Patronizing and Condescending Language Detection (2024)

Abstract: 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 essential branch of toxic language, this type of language exacerbates conflicts and confrontations among Internet communities and detrimentally impacts disadvantaged groups. Traditional pre-trained language models (PLMs) perform poorly in detecting PCL due to its implicit toxicity traits like hypocrisy and false sympathy. With the rise of large language models (LLMs), we can harness their rich emotional semantics to establish a paradigm for exploring implicit toxicity. In this paper, we introduce PclGPT, a comprehensive LLM benchmark designed specifically for PCL. We collect, annotate, and integrate the Pcl-PT/SFT dataset, and then develop a bilingual PclGPT-EN/CN model group through a comprehensive pre-training and supervised fine-tuning staircase process to facilitate implicit toxic detection. Group detection results and fine-grained detection from PclGPT and other models reveal significant variations in the degree of bias in PCL towards different vulnerable groups, necessitating increased societal attention to protect them.

## introduction patronizing and condescending language (pcl) specifically targets vulnerable groups. as an important but underexplored branch of toxic language, timely detection of pcl is crucial for protecting disadvantaged communities from further exclusion and inequality. unlike traditional toxic languages such as hate speech @xcite and offensive language @xcite @xcite , pcl expressions are more subtle and implicit (e.g., " these poor children! it's truly admirable how they keep striving despite their humble beginnings."). this example is interesting because the original intention of pcl might have been to positively describe efforts to improve the lives of disadvantaged groups. however, it ultimately conveys subtle arrogance and discrimination, harming the individuals being sympathized with. figure 1 : scatter plots for the scores using the perspective api @xcite on the hate and pcl datasets. the left plot shows the english datasets semeval-19 (hate) and semeval-22 (pcl), while the right plot shows the chinese datasets cold (hate) and ccpc (pcl). the toxicity score ranges from 0 to 1, with increasing toxicity as discrete values. the subtle toxicity of pcl is further illustrated through toxicity scores. we compared the pcl and hate datasets in both english and chinese domains. as shown in figure 1 , in both chinese and english corpora, the toxicity scores of pcl are much lower than those of hate speech. this is due to the ambiguous toxic semantic features of pcl, which often lack explicit attacking vocabulary, leading to plms struggling to achieve optimal detection performance. the absence of high-quality data further constrains this field @xcite . large language models (llms) offer new opportunities with their extensive pre-trained knowledge and enhanced capability in revealing toxicity @xcite . however, they still english task pcl category plms gpt4.0 pclgpt-en since the elderly have been placed in a nursing home, they are undoubtedly left unattended most of the time. ## pclgpt the overall approach is illustrated in figure 2 . our pclgpt model group consists of two sub-models: pclgpt-en and pclgpt-cn, using llama-2-7b and chatglm-3-6b @xcite as their base architectures, respectively. llama, one of the foremost english open-source llms today, has been pre-trained on over 20 trillion tokens. chat-glm, among the most advanced chinese llms, is built upon the generalized linear model (glm) architecture and has been extensively optimized for chinese question-answering and dialogue tasks, exhibiting outstanding performance in the chinese domain. llama-2-7b has a context length of up to 4096 tokens and chatglm-3-6b with 8192 tokens, ensuring a thorough understanding of the context. detailed descriptions of the pre-training and finetuning stages will be provided in the subsequent sections. ## limitation pcl is a subclass of microaggressions within toxic language. due to the limited research in this area, further linguistic foundation is needed to refine the standardized definition of this type of speech. our current study lacks an examination of "false positive" cases, such as insincere benevolence and superficial compliments directed at marginalized communities