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cs.SD2026

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection

Yanqiu Li, Yang Xiao, Jisheng Bai +3

Recent advances in speech synthesis and audio generation have made high-fidelity acoustic forgery low-cost and difficult to attribute, enabling a realistic attack scenario in which…

cs.SD2026

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

Hongyu Jin, Siyi Wang, Yang Xiao +10

Humans process rich auditory environments through tightly integrated cognitive capabilities such as audio perception, audio reasoning, and memory. Despite recent progress in large…

cs.SD2026

The First Environmental Sound Deepfake Detection Challenge: Benchmarking Robustness, Evaluation, and Insights

Han Yin, Yang Xiao, Rohan Kumar Das +2

Recent progress in audio generation has made it increasingly easy to create highly realistic environmental soundscapes, which can be misused to produce deceptive content, such as f…

cs.SD2026

Focus Then Listen: An Empirical Study of Plug-and-Play Audio Enhancer for Noise-Robust Large Audio Language Models

Han Yin, Yang Xiao, Younghoo Kwon +2

Large audio language models (LALMs) are a class of foundation models for audio understanding. Existing LALMs tend to degrade significantly in real-world noisy acoustic conditions w…

cs.SD2025

Temporally Heterogeneous Graph Contrastive Learning for Multimodal Acoustic event Classification

Yuanjian Chen, Yang Xiao, Jinjie Huang

Multimodal acoustic event classification plays a key role in audio-visual systems. Although combining audio and visual signals improves recognition, it is still difficult to align…

cs.SD2025

Noise-Robust Sound Event Detection and Counting via Language-Queried Sound Separation

Yuanjian Chen, Yang Xiao, Han Yin +2

Most sound event detection (SED) systems perform well on clean datasets but degrade significantly in noisy environments. Language-queried audio source separation (LASS) models show…