activity
20242026
collaborators

15 papers

eess.AS2026

Improving Text-to-Audio Instruction Following via Fine-Grained Feedback from Audio-Aware Large Language Models

Chun-Yi Kuan, Siwon Kim, Byeonggeun Kim +8

The paper proposes using audio-aware large language models to give fine‑grained feedback on text‑to‑audio generation, improving how well the generated audio follows multi‑event and…

eess.AS2026

The Sound of Absence: Audio-Language Embedding Models Struggle with Negation

Chun-Yi Kuan, Hung-yi Lee

The paper reveals that audio-language embedding models like CLAP cannot distinguish between present and absent sound events, showing they treat negated captions similarly to affirm…

eess.AS2026

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…

eess.AS2026

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

Kai-Wei Chang, En-Pei Hu, Chun-Yi Kuan +7

Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of temporal dynamics, including the abil…

eess.AS2026

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…

eess.AS2026

DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment

Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25

We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…