We cannot overemphasize the essence of contextual information in most natural language
processing (NLP) applications. The extraction of context yields significant improvements in …

Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

Large neural networks can now generate jokes, but do they really" understand" humor? We
challenge AI models with three tasks derived from the New Yorker Cartoon Caption Contest …

Recognizing humor from a video utterance requires understanding the verbal and non-
verbal components as well as incorporating the appropriate context and external …

Despite recent advances in information retrieval and natural language processing, rhetorical
devices that exploit ambiguity or subvert linguistic rules remain a challenge for such …

While humour and wordplay are among the most intensively studied problems in the field of
translation studies, they have been almost completely ignored in machine translation. This is …

Humour is a substantial element of human affect and cognition. Its automatic understanding
can facilitate a more naturalistic human-device interaction and the humanisation of artificial …

In this study, we focus on automatic humor detection, a highly relevant task for
conversational AI. To date, there are several English datasets for this task, but little research …

Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable
performance in a wide range of tasks. Despite numerous recent studies that examine the …

Humor recognition in conversations is a challenging task that has recently gained popularity
due to its importance in dialogue understanding, including in multimodal settings (ie, text …