3 papers
cs.CL2025
Do Audio LLMs Really LISTEN, or Just Transcribe? Measuring Lexical vs. Acoustic Emotion Cues Reliance
Jingyi Chen, Zhimeng Guo, Jiyun Chun +3
Understanding emotion from speech requires sensitivity to both lexical and acoustic cues. However, it remains unclear whether large audio language models (LALMs) genuinely process…
cs.DC2025
Equinox: Holistic Fair Scheduling in Serving Large Language Models
Zhixiang Wei, James Yen, Jingyi Chen +11
We address the limitations of current LLM serving with a dual-counter framework separating user and operator perspectives. The User Fairness Counter measures quality of service via…
cs.SD2025
Fine-Tuning Text-to-Speech Diffusion Models Using Reinforcement Learning with Human Feedback
Jingyi Chen, Ju Seung Byun, Micha Elsner +2
Diffusion models produce high-fidelity speech but are inefficient for real-time use due to long denoising steps and challenges in modeling intonation and rhythm. To improve this, w…