Papers by Kangwook Ko
Generalizable Prompt Tuning for Audio-Language Models via Semantic Expansion (2026.findings-acl)
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| Challenge: | Prompt tuning has achieved remarkable progress in vision–language models, but its generalization ability in ALMs remains underexplored. |
| Approach: | They propose a plug-and-play framework that regularizes the prompt embedding space . they propose introducing a semantic expansion loss with margin constraints that promote compactness . |
| Outcome: | The proposed framework regularizes the prompt embedding space by incorporating semantic neighbors generated by large language models. |