Abstract Chain-of-Thought (CoT) guides large language models (LLMs) to reason step-by-
step and can motivate their logical reasoning ability. While effective for logical tasks CoT is …

This paper describes the SemEval-2020 shared task" Assessing Humor in Edited News
Headlines." The task's dataset contains news headlines in which short edits were applied to …

Humor is a substantial element of human social behavior, affect, and cognition. Its automatic
understanding can facilitate a more naturalistic human-AI interaction. Current methods of …

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 …

Column Editor's note: Machine generation and comprehension of language is a difficult
enough task, but it's not even funny how difficult it is for a machine to produce and detect …

In this work, we combine the state-of-the-art BERT architecture with the semi-supervised
learning technique UDA in order to exploit unlabeled raw data to assess humor and detect …

Understanding and identifying humor has been increasingly popular, as seen by the number
of datasets created to study humor. However, one area of humor research, humor …

The automatic detection of humor poses a grand challenge for natural language processing.
Transformer-based systems have recently achieved remarkable results on this task, but they …

Large pre-trained transformer-based language models have revolutionized the field of
natural language processing in recent years. While BERT-like models perform exceptionally …

An effective task-oriented chatbot should be able to exert a certain level of Social
Intelligence (SI), the ability to emulate human social behaviors to reduce user frustration and …