24 citations · 32 across the 23 of their papers we have counts for
8 papers · 1 filter
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…
PSA-MF: Personality-Sentiment Aligned Multi-Level Fusion for Multimodal Sentiment Analysis
Heng Xie, Kang Zhu, Zhengqi Wen +4
Multimodal sentiment analysis (MSA) is a research field that recognizes human sentiments by combining textual, visual, and audio modalities. The main challenge lies in integrating…
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…
RPRA-ADD: Forgery Trace Enhancement-Driven Audio Deepfake Detection
Ruibo Fu, Xiaopeng Wang, Zhengqi Wen +8
Existing methods for deepfake audio detection have demonstrated some effectiveness. However, they still face challenges in generalizing to new forgery techniques and evolving attac…
MER 2025: When Affective Computing Meets Large Language Models
Zheng Lian, Rui Liu, Kele Xu +15
MER2025 is the third year of our MER series of challenges, aiming to bring together researchers in the affective computing community to explore emerging trends and future direction…
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…