This joke is [MASK]: Recognizing Humor and Offense with Prompting

Li, Junze; Zhao, Mengjie; Xie, Yubo; Maronikolakis, Antonis; Pu, Pearl and Schütze, Hinrich (2023): This joke is [MASK]: Recognizing Humor and Offense with Prompting. 1st Transfer Learning for Natural Language Processing Workshop, New Orleans, Louisiana, USA, 03 December 2022. Proceedings of Machine Learning Research. Vol. 203 pp. 1-9

Abstract

Humor is a magnetic component in everyday human interactions and communications. Computationally modeling humor enables NLP systems to entertain and engage with users. We investigate the effectiveness of prompting, a new transfer learning paradigm for NLP, for humor recognition. We show that prompting performs similarly to finetuning when numerous annotations are available, but gives stellar performance in low-resource humor recognition. The relationship between humor and offense is also inspected by applying influence functions to prompting; we show that models could rely on offense to determine humor during transfer.

• Item Type: Conference or Workshop Item (Paper)
• EU Funded Grant Agreement Number: 740516
• EU Projects: Horizon 2020 > ERC Grants > ERC Advanced Grant > ERC Grant 740516: NonSequeToR - Non-sequence models for tokenization replacement
• Research Centers: Center for Information and Language Processing (CIS)
• Subjects: 400 Language > 400 Language; 400 Language > 410 Linguistics
• Language: English