Hyebin Cho

Text dominance in Audio LLMs can be mitigated through a novel back-patching technique that enhances audio representations, challenging the status quo of multimodal processing.

Integrating trainable prompts into the audio encoder can significantly boost few-shot learning performance in Audio-Language Models, outperforming traditional text-only approaches.