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Thai Humor Generation by Small Language Models

Published in ECTI-CON 2025, 2025

Generating humor that aligns with Thai cultural and linguistic nuances is challenging for generative AI. This paper addresses this by fine-tuning small language models (SLMs) on high-quality, non-synthetic Thai humor datasets. The Llama-3.2-3B model and Low-Rank Adaptation (LoRA) were used for efficient parameter tuning. A comprehensive evaluation with Thai participants ensured the generated humor resonated with cultural expectations.

Recommended citation: Poobanchean, P., Chaithong, S., Muansuwan, N., Limseelo, C., Sirinaovakul, B., & Suwannahong, K. (2025). Thai Humor Generation by Small Language Models. King Mongkut’s University of Technology Thonburi.
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teaching

Teaching Assistant for CPE123: UX/UI Course

Undergraduate course, Computer Engineering - King Mongkut's University of Technology Thonburi, 2023

For this teaching experience, I have been invited to the course as the guest lecturer for teaching core web vitals, the good UX/UI design for web development, which is totally impacted to the developers to have a good responsibility on designing web application. The lecture that I have been discussed was about lazy loading, containers, and divider of the page content, along with some factors in the development and design.