1 citations · 1 across the 12 of their papers we have counts for
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MoLT: Mixture of Layer-Wise Tokens for Efficient Audio-Visual Learning
Kyeongha Rho, Hyeongkeun Lee, Jae Won Cho +1
In this paper, we propose Mixture of Layer-Wise Tokens (MoLT), a parameter- and memory-efficient adaptation framework for audio-visual learning. The key idea of MoLT is to replace…
Diffusion-Link: Diffusion Probabilistic Model for Bridging the Audio-Text Modality Gap
KiHyun Nam, Jongmin Choi, Hyeongkeun Lee +2
Contrastive audio-language pretraining yields powerful joint representations, yet a persistent audio-text modality gap limits the benefits of coupling multimodal encoders with larg…
LAVCap: LLM-based Audio-Visual Captioning using Optimal Transport
Kyeongha Rho, Hyeongkeun Lee, Valentio Iverson +1
Automated audio captioning is a task that generates textual descriptions for audio content, and recent studies have explored using visual information to enhance captioning quality.…