Research
My primary research interest lies in the creativity of Large Language Models (LLMs). I explore how LLMs can generate creative and attractive text across various domains, including ad text generation, summarization, and data-to-text applications.
I also work on understanding what makes text attractive or appealing, particularly in advertising contexts, as well as computational approaches to humor understanding and generation.
Research Areas
Natural Language Generation
Text generation with LLMs: ads, summaries, and data-to-text
Computational Advertising
Analysis and generation of advertising texts
Humor Understanding
Computational understanding and generation of humor
Projects
Ad Text Generation
Research on automatically generating attractive ad texts using LLMs. Extracting and utilizing effective appeal expressions from landing page information.
Attractive Expression Analysis
Building and analyzing datasets of ad text paraphrase pairs to study the characteristics of attractive expressions.
Humor Understanding
Benchmark construction for humor understanding through Oogiri tasks and analysis of user preferences.
Research Keywords
Collaboration
At CyberAgent AI Lab, I conduct applied research in collaboration with advertising delivery platforms. Through joint research with Okumura Laboratory at Institute of Science Tokyo, I engage in a wide range of work from fundamental research to practical applications.