7 papers
AT-ADD: All-Type Audio Deepfake Detection Challenge Evaluation Plan
Yuankun Xie, Haonan Cheng, Jiayi Zhou +10
The rapid advancement of Audio Large Language Models (ALLMs) has enabled cost-effective, high-fidelity generation and manipulation of both speech and non-speech audio, including so…
Towards Explicit Acoustic Evidence Perception in Audio LLMs for Speech Deepfake Detection
Xiaoxuan Guo, Yuankun Xie, Haonan Cheng +5
Speech deepfake detection (SDD) focuses on identifying whether a given speech signal is genuine or has been synthetically generated. Existing audio large language model (LLM)-based…
Detect All-Type Deepfake Audio: Wavelet Prompt Tuning for Enhanced Auditory Perception
Yuankun Xie, Ruibo Fu, Zhiyong Wang +5
The rapid advancement of audio generation technologies has escalated the risks of malicious deepfake audio across speech, sound, singing voice, and music, threatening multimedia se…
EnvSSLAM-FFN: Lightweight Layer-Fused System for ESDD 2026 Challenge
Xiaoxuan Guo, Hengyan Huang, Jiayi Zhou +5
Recent advances in generative audio models have enabled high-fidelity environmental sound synthesis, raising serious concerns for audio security. The ESDD 2026 Challenge therefore…
Noise-Informed Diffusion-Generated Image Detection with Anomaly Attention
Weinan Guan, Wei Wang, Bo Peng +3
With the rapid development of image generation technologies, especially the advancement of Diffusion Models, the quality of synthesized images has significantly improved, raising c…
The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio
Yuankun Xie, Yi Lu, Ruibo Fu +9
With the proliferation of Audio Language Model (ALM) based deepfake audio, there is an urgent need for generalized detection methods. ALM-based deepfake audio currently exhibits wi…