activity
20242026
collaborators

16 papers

cs.CL2026

XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models

Yupei Li, Qiyang Sun, Xiaoliang Wu +3

Speech deepfake detection (SDD) systems require trustworthy explanations for reliable decision-making. Existing explanation ways mainly fall into two categories. Traditional explai…

cs.SD2026

Explainable Detection of Machine Generated Music and Early Systematic Evaluation

Yupei Li, Qiyang Sun, Hanqian Li +2

Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within th…

cs.SD2026

Enhancing Efficiency and Performance in Deepfake Audio Detection through Neuron-level Dropin & Neuroplasticity Mechanisms

Yupei Li, Shuaijie Shao, Manuel Milling +1

Current audio deepfake detection has achieved remarkable performance using diverse deep learning architectures such as ResNet, and has seen further improvements with the introducti…

cs.SD2026

M6: Multi-generator, Multi-domain, Multi-lingual and cultural, Multi-genres, Multi-instrument Machine-Generated Music Detection Databases

Yupei Li, Hanqian Li, Lucia Specia +1

Machine-generated music (MGM) has emerged as a powerful tool with applications in music therapy, personalised editing, and creative inspiration for the music community. However, it…

cs.LG2026

Affect and Effect: Limitations of regularisation-based continual learning in EEG-based emotion classification

Nina Peire, Yupei Li, Björn Schuller

Generalisation to unseen subjects in EEG-based emotion classification remains a challenge due to high inter-and intra-subject variability. Continual learning (CL) poses a promising…

cs.SD2025

DFALLM: Achieving Generalizable Multitask Deepfake Detection by Optimizing Audio LLM Components

Yupei Li, Li Wang, Yuxiang Wang +5

Audio deepfake detection has recently garnered public concern due to its implications for security and reliability. Traditional deep learning methods have been widely applied to th…