mlsanityData to 14 Oct 2026

Not All Jokes Land: Evaluating Large Language Models Understanding of Workplace Humor

arXiv 2506.01819 ↗First posted 2 Jun 2025cs.CL cs.CYcited by 6

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Abstract (arXiv)

With the recent advances in Artificial Intelligence (AI) and Large Language Models (LLMs), the automation of daily tasks, like automatic writing, is getting more and more attention. Hence, efforts have focused on aligning LLMs with human values, yet humor, particularly professional industrial humor used in workplaces, has been largely neglected. To address this, we develop a dataset of professional humor statements along with features that determine the appropriateness of each statement. Our evaluation of five LLMs shows that LLMs often struggle to judge the appropriateness of humor accurately.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 10 of its 38 references that are in the map. First posted on arXiv 2 Jun 2025.

Builds on

10 of 38 references.

References · 10

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  3. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  4. 2024Qwen2 Technical Reportcited by 2,120
  5. 2023Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generationcited by 56
  6. 2023COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statementscited by 34
  7. 2024BertaQA: How Much Do Language Models Know About Local Culture?cited by 23
  8. 2024Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Mediacited by 14
  9. 2024Small But Funny: A Feedback-Driven Approach to Humor Distillationcited by 12
  10. 2024Humor Mechanics: Advancing Humor Generation with Multistep Reasoningcited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.