Papers by Joohyun Chang
SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter (2026.acl-long)
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| Challenge: | Existing approaches to understanding laughter or humor focus on narrowly defined tasks such as detecting humor and estimating humor intensity. |
| Approach: | They propose a dataset for real-world laughter understanding with multimodal textual representations and question–answer annotations. |
| Outcome: | The proposed framework outperforms baselines in three laughter-related tasks, showing that it is robust. |