Can Li, Bin Pang, Wenbo Wang, Lingshu Hu, Matthew Gordon, Detelina Marinova, Bitty Balducci, Yi Shang
{"title":"语言模型如何理解礼貌?","authors":"Can Li, Bin Pang, Wenbo Wang, Lingshu Hu, Matthew Gordon, Detelina Marinova, Bitty Balducci, Yi Shang","doi":"10.1109/cai54212.2023.00106","DOIUrl":null,"url":null,"abstract":"Politeness plays a key role in social communications. Previous work proposed an SVM-based computational method for predicting politeness using linguistic features on a corpus that contains Wikipedia and Stack Exchange requests data. To extend this prior work, we focus on evaluating the performance of state-of-the-art language models on politeness prediction using the same dataset. Two models are applied in this study. First, we fine-tune BERT on politeness data and then use the fine-tuned model for politeness prediction. Second, we use ChatGPT to predict politeness. The results show that both fine-tuned BERT and ChatGPT achieved better results than the state-of-the-art results on both Wikipedia and Stack Exchange data. Fine-tuned BERT outperforms zero shot ChatGPT, but ChatGPT can provide explanations for its prediction. Moreover, fine-tuned BERT outperforms human-level performance by 2.28% on Wikipedia corpus.","PeriodicalId":129324,"journal":{"name":"2023 IEEE Conference on Artificial Intelligence (CAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How Well Can Language Models Understand Politeness?\",\"authors\":\"Can Li, Bin Pang, Wenbo Wang, Lingshu Hu, Matthew Gordon, Detelina Marinova, Bitty Balducci, Yi Shang\",\"doi\":\"10.1109/cai54212.2023.00106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Politeness plays a key role in social communications. Previous work proposed an SVM-based computational method for predicting politeness using linguistic features on a corpus that contains Wikipedia and Stack Exchange requests data. To extend this prior work, we focus on evaluating the performance of state-of-the-art language models on politeness prediction using the same dataset. Two models are applied in this study. First, we fine-tune BERT on politeness data and then use the fine-tuned model for politeness prediction. Second, we use ChatGPT to predict politeness. The results show that both fine-tuned BERT and ChatGPT achieved better results than the state-of-the-art results on both Wikipedia and Stack Exchange data. Fine-tuned BERT outperforms zero shot ChatGPT, but ChatGPT can provide explanations for its prediction. Moreover, fine-tuned BERT outperforms human-level performance by 2.28% on Wikipedia corpus.\",\"PeriodicalId\":129324,\"journal\":{\"name\":\"2023 IEEE Conference on Artificial Intelligence (CAI)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Conference on Artificial Intelligence (CAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/cai54212.2023.00106\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Conference on Artificial Intelligence (CAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cai54212.2023.00106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How Well Can Language Models Understand Politeness?
Politeness plays a key role in social communications. Previous work proposed an SVM-based computational method for predicting politeness using linguistic features on a corpus that contains Wikipedia and Stack Exchange requests data. To extend this prior work, we focus on evaluating the performance of state-of-the-art language models on politeness prediction using the same dataset. Two models are applied in this study. First, we fine-tune BERT on politeness data and then use the fine-tuned model for politeness prediction. Second, we use ChatGPT to predict politeness. The results show that both fine-tuned BERT and ChatGPT achieved better results than the state-of-the-art results on both Wikipedia and Stack Exchange data. Fine-tuned BERT outperforms zero shot ChatGPT, but ChatGPT can provide explanations for its prediction. Moreover, fine-tuned BERT outperforms human-level performance by 2.28% on Wikipedia corpus.