How capable are state-of-the-art language models to cope with sarcasm?

Author:

Băroiu Alexandru -Costin1,Trăuşan-Matu Ştefan1

Affiliation:

1. Politehnica University of Bucharest,Faculty of Automatic Control and Computer Science,Bucharest,Romania

Publisher

IEEE

Reference17 articles.

1. RoBERTa: A Robustly Optimized BERT Pretraining Approach;liu;ArXiv,2019

2. Clinical Insights into Pragmatic Theory: Frontal Lobe Deficits and Sarcasm

3. Language models are few-shot learners;brown;Advances in neural information processing systems,2020

4. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations;lan;arXiv 1909 11942,2019

5. Evaluation of OpenAI’s large language model as a new tool for writing papers in the field of thrombosis and hemostasis

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sarcasm Detection in Chinese and English Text with Fine-Tuned Large Language Models;2024 IEEE 10th Conference on Big Data Security on Cloud (BigDataSecurity);2024-05-10

2. Revisiting Challenges and Hazards in Large Language Model Evaluation;PROCES LENG NAT;2024

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