Author

Hong-Yu Jin

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#artificial intelligence Jun 2026

RAIL: Rethinking Auditory Intelligence in Large Audio-Language Models with a CHC-Grounded Benchmark

RAIL is introduced, a human-centric benchmark grounded in the Cattell--Horn--Carroll (CHC) framework, which formalises auditory cognition into five core capabilities, and develops them into structured evaluation tasks with principled data curation and human-aligned evaluation protocols.

Hong-Yu Jin, Siyi Wang, Yang Xiao et al. · arXiv.org · 3 citations

#artificial intelligence Preprint Sep 2026

ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models

Experiments show that ER-EDF consistently improves empathetic response quality in both automatic and human evaluations, highlighting the importance of jointly modeling emotion perception and regulation in spoken empathetic dialogue systems, paving a new direction for psychologically grounded empathetic AI.

Hong-Yu Jin, Wen-Da Zhang, Run-Qiu Fei et al. · 0 citations