7 citations · 10 across the 22 of their papers we have counts for
5 papers · 1 filter
Improving Text-to-Audio Instruction Following via Fine-Grained Feedback from Audio-Aware Large Language Models
Chun-Yi Kuan, Siwon Kim, Byeonggeun Kim +7
Recent text-to-audio models generate high-quality audio, but often fail to follow instructions involving multiple sound events and temporal order. This gap arises because existing…
The Sound of Absence: Audio-Language Embedding Models Struggle with Negation
Chun-Yi Kuan, Hung-yi Lee
Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-only evaluation hides a key lim…
Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models
Chun-Yi Kuan, Wei-Ping Huang, Hung-yi Lee
Recent audio-aware large language models (ALLMs) have demonstrated strong capabilities across diverse audio understanding and reasoning tasks, but they still frequently produce hal…
AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering
Chun-Yi Kuan, Kai-Wei Chang, Hung-yi Lee
Although text-to-audio generation has made remarkable progress in realism and diversity, the development of evaluation metrics has not kept pace. Widely-adopted approaches, typical…
AQUA-Bench: Beyond Finding Answers to Knowing When There Are None in Audio Question Answering
Chun-Yi Kuan, Hung-yi Lee
Recent advances in audio-aware large language models have shown strong performance on audio question answering. However, existing benchmarks mainly cover answerable questions and o…