Zobrazeno 1 - 10
of 3 945
pro vyhledávání: '"Sarcasm detection"'
Autor:
Gao, Xiyuan, Bansal, Shubhi, Gowda, Kushaan, Li, Zhu, Nayak, Shekhar, Kumar, Nagendra, Coler, Matt
Detecting sarcasm effectively requires a nuanced understanding of context, including vocal tones and facial expressions. The progression towards multimodal computational methods in sarcasm detection, however, faces challenges due to the scarcity of d
Externí odkaz:
http://arxiv.org/abs/2412.10103
Sarcasm detection is a significant challenge in sentiment analysis due to the nuanced and context-dependent nature of verbiage. We introduce Pragmatic Metacognitive Prompting (PMP) to improve the performance of Large Language Models (LLMs) in sarcasm
Externí odkaz:
http://arxiv.org/abs/2412.04509
Autor:
Guo, Diandian, Cao, Cong, Yuan, Fangfang, Liu, Yanbing, Zeng, Guangjie, Yu, Xiaoyan, Peng, Hao, Yu, Philip S.
Multimodal sarcasm detection (MSD) is essential for various downstream tasks. Existing MSD methods tend to rely on spurious correlations. These methods often mistakenly prioritize non-essential features yet still make correct predictions, demonstrati
Externí odkaz:
http://arxiv.org/abs/2412.00756
Sarcasm is hard to interpret as human beings. Being able to interpret sarcasm is often termed as a sign of intelligence, given the complex nature of sarcasm. Hence, this is a field of Natural Language Processing which is still complex for computers t
Externí odkaz:
http://arxiv.org/abs/2412.00425
Sarcasm is a rhetorical device that is used to convey the opposite of the literal meaning of an utterance. Sarcasm is widely used on social media and other forms of computer-mediated communication motivating the use of computational models to identif
Externí odkaz:
http://arxiv.org/abs/2410.18882
Autor:
Đoković, Lazar, Robnik-Šikonja, Marko
Publikováno v:
Proceedings of the 27th International Multiconference INFORMATION SOCIETY - IS 2024, Volume A, 2024, pages 19-22
The sarcasm detection task in natural language processing tries to classify whether an utterance is sarcastic or not. It is related to sentiment analysis since it often inverts surface sentiment. Because sarcastic sentences are highly dependent on co
Externí odkaz:
http://arxiv.org/abs/2410.12704
Autor:
Yu, Bengong1,2 (AUTHOR) bgyu@hfut.edu.cn, Ji, Xiaohan1 (AUTHOR)
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 2024, Vol. 46 Issue 4, p8361-8374. 14p.
Sarcasm is a type of irony, characterized by an inherent mismatch between the literal interpretation and the intended connotation. Though sarcasm detection in text has been extensively studied, there are situations in which textual input alone might
Externí odkaz:
http://arxiv.org/abs/2408.02595
Publikováno v:
Journal of Communications Software and Systems, Vol 20, Iss 4, Pp 278-289 (2024)
Recent years have seen a notable rise in online opinion-sharing, underscoring the demand for automated sentiment analysis tools. Addressing sarcasm in text is crucial, as it can significantly influence the effectiveness of sentiment analysis models.
Externí odkaz:
https://doaj.org/article/6c94715d66ab46d590473204f5a5d265
Elaborating a series of intermediate reasoning steps significantly improves the ability of large language models (LLMs) to solve complex problems, as such steps would evoke LLMs to think sequentially. However, human sarcasm understanding is often con
Externí odkaz:
http://arxiv.org/abs/2407.12725