works on

From the 1 of 11 linked papers with an AI index.

activity
20242026
collaborators

11 papers

cs.SD2026

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection

Qiyang Sun, Yi Chang, Yupei Li +3

The paper introduces CHARM, a training-free framework that calibrates large language model predictions and fuses prosodic acoustic cues to improve zero-shot multimodal sarcasm dete…

cs.SD2026

SIGMA: Saliency-Guided Sparse Mask Attacks for Speech Emotion Recognition

Qiyang Sun, Yi Chang, Zixing Zhang +1

Speech conveys rich emotional information. As Speech Emotion Recognition (SER) is usually deployed in privacy-sensitive and reliability-critical environments, adversarial attacks o…

cs.AI2026

Towards Dys-XAI: Influence-Based Explanations for Dysarthria Severity Assessment

Xiaoliang Wu, Qiyang Sun, Yupei Li +3

Dysarthria severity assessment is essential for therapy planning and longitudinal monitoring, yet manual perceptual rating is time-consuming and variable across clinicians. Althoug…

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.LG2025

RAxSS: Retrieval-Augmented Sparse Sampling for Explainable Variable-Length Medical Time Series Classification

Aydin Javadov, Samir Garibov, Tobias Hoesli +4

Medical time series analysis is challenging due to data sparsity, noise, and highly variable recording lengths. Prior work has shown that stochastic sparse sampling effectively han…