1 citations · 1 across the 6 of their papers we have counts for
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LAMB: LLM-based Audio Captioning with Modality Gap Bridging via Cauchy-Schwarz Divergence
Hyeongkeun Lee, Jongmin Choi, KiHyun Nam +1
Automated Audio Captioning aims to describe the semantic content of input audio. Recent works have employed large language models (LLMs) as a text decoder to leverage their reasoni…
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…