7 papers
M3-TTS: Multi-modal DiT Alignment & Mel-latent for Zero-shot High-fidelity Speech Synthesis
Xiaopeng Wang, Chunyu Qiang, Ruibo Fu +10
Non-autoregressive (NAR) text-to-speech synthesis relies on length alignment between text sequences and audio representations, constraining naturalness and expressiveness. Existing…
Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning
Kaiying Yan, Moyang Liu, Yukun Liu +4
The rapid spread of fake news across multimedia platforms presents serious challenges to information credibility. In this paper, we propose a Debunk-and-Infer framework for Fake Ne…
Deconfounded Reasoning for Multimodal Fake News Detection via Causal Intervention
Moyang Liu, Kaiying Yan, Yukun Liu +4
The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, and video. Traditional unimodal…
Exploring Modality Disruption in Multimodal Fake News Detection
Moyang Liu, Kaiying Yan, Yukun Liu +4
The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, and video. Compared to unimodal…
MTPareto: A MultiModal Targeted Pareto Framework for Fake News Detection
Kaiying Yan, Moyang Liu, Yukun Liu +5
Multimodal fake news detection is essential for maintaining the authenticity of Internet multimedia information. Significant differences in form and content of multimodal informati…
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…