1 citations · 4 across the 15 of their papers we have counts for
16 papers
When Semantics Matter: Reliability-Aware Semantic-Rhythm Control for Co-Speech Gesture Generation
Zhirui Xing, Long Ye, Kaige Li +2
Co-speech gesture generation aims to synthesize natural gestures that are both temporally synchronized with speech and semantically consistent with the spoken content. Although rec…
AT-ADD: A Benchmark and Challenge for Robust and All-Type Audio Deepfake Detection
Yuankun Xie, Haonan Cheng, Jiayi Zhou +12
Recent audio generation models can synthesize high-fidelity speech, environmental sound, singing voice, and music, creating new risks for multimedia trust. Existing audio deepfake…
AT-ADD: All-Type Audio Deepfake Detection Challenge Summary
Yuankun Xie, Haonan Cheng, Jiayi Zhou +11
This paper summarizes the ACM Multimedia 2026 AT-ADD Grand Challenge on all-type audio deepfake detection. AT-ADD contains two tracks: robust speech deepfake detection under realis…
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…
Interpretable All-Type Audio Deepfake Detection with Audio LLMs via Frequency-Time Reinforcement Learning
Yuankun Xie, Xiaoxuan Guo, Jiayi Zhou +6
Recent advances in audio large language models (ALLMs) have made high-quality synthetic audio widely accessible, increasing the risk of malicious audio deepfakes across speech, env…
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…
Fake Speech Wild: Detecting Deepfake Speech on Social Media Platform
Yuankun Xie, Ruibo Fu, Xiaopeng Wang +5
The rapid advancement of speech generation technology has led to the widespread proliferation of deepfake speech across social media platforms. While deepfake audio countermeasures…
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…
MAG: Multi-Modal Aligned Autoregressive Co-Speech Gesture Generation without Vector Quantization
Binjie Liu, Lina Liu, Sanyi Zhang +5
This work focuses on full-body co-speech gesture generation. Existing methods typically employ an autoregressive model accompanied by vector-quantized tokens for gesture generation…
Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set Condition
Yuankun Xie, Xiaopeng Wang, Zhiyong Wang +7
Current research in audio deepfake detection is gradually transitioning from binary classification to multi-class tasks, referred as audio deepfake source tracing task. However, ex…
A Contemporary Overview: Trends and Applications of Large Language Models on Mobile Devices
Lianjun Liu, Hongli An, Pengxuan Chen +1
With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural…
Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?
Yuankun Xie, Chenxu Xiong, Xiaopeng Wang +9
Currently, Audio Language Models (ALMs) are rapidly advancing due to the developments in large language models and audio neural codecs. These ALMs have significantly lowered the ba…
Temporal Variability and Multi-Viewed Self-Supervised Representations to Tackle the ASVspoof5 Deepfake Challenge
Yuankun Xie, Xiaopeng Wang, Zhiyong Wang +4
ASVspoof5, the fifth edition of the ASVspoof series, is one of the largest global audio security challenges. It aims to advance the development of countermeasure (CM) to discrimina…
Generalized Source Tracing: Detecting Novel Audio Deepfake Algorithm with Real Emphasis and Fake Dispersion Strategy
Yuankun Xie, Ruibo Fu, Zhengqi Wen +5
With the proliferation of deepfake audio, there is an urgent need to investigate their attribution. Current source tracing methods can effectively distinguish in-distribution (ID)…
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…