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Summary of Innovative Thinking, Infinite Humor: Humor Research Of Large Language Models Through Structured Thought Leaps, by Han Wang et al.


Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps

by Han Wang, Yilin Zhao, Dian Li, Xiaohan Wang, Gang Liu, Xuguang Lan, Hui Wang

First submitted to arxiv on: 14 Oct 2024

Categories

  • Main: Artificial Intelligence (cs.AI)
  • Secondary: None

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
The proposed Creative Leap of Structured Thought (CLoST) framework tackles the challenge of humor generation, which requires creativity, strong associative thinking, and continuous reflection. Unlike the Creative Leap-of-Thought (CLoT) paradigm, CLoST focuses on structured thought to generate humor content. To achieve this, a reward model is designed to correct errors, as there is currently no expert model of humor or usable rule to determine whether content is humorous. The framework includes judgement-oriented instructions to improve the model’s capability and an open-domain instruction evolutionary method to fully unleash its potential. Through reinforcement learning, the model learns to refine its strategies, recognize and correct mistakes, and generate creative answers.
Low GrooveSquid.com (original content) Low Difficulty Summary
Humor is a tricky thing! It’s hard for computers to understand why something is funny because humor is so culturally dependent. Computers are great at solving math problems, but they need help generating jokes. This paper proposes a new way of thinking about making people laugh, which it calls the Creative Leap of Structured Thought (CLoST). The idea is that by structuring our thoughts, we can create humor that makes sense. To do this, the team designed a special reward system to help computers learn from their mistakes and get better at generating jokes over time.

Keywords

» Artificial intelligence  » Reinforcement learning