2025

Biting Off More Than You Can Detect: Retrieval-Augmented Multimodal Experts for Short Video Hate Detection
Biting Off More Than You Can Detect: Retrieval-Augmented Multimodal Experts for Short Video Hate Detection

Jian Lang, Rongpei Hong, Jin Xu, Xovee Xu, Yili Li, Fan Zhou

The Web Conference (WWW) 2025 CCF-A Full Paper

We introduce MoRE (Mixture of Retrieval-augmented multimodal Experts), a novel framework designed to enhance short video hate detection.

[Paper] [Code]

Biting Off More Than You Can Detect: Retrieval-Augmented Multimodal Experts for Short Video Hate Detection

Jian Lang, Rongpei Hong, Jin Xu, Xovee Xu, Yili Li, Fan Zhou

The Web Conference (WWW) 2025 CCF-A Full Paper

We introduce MoRE (Mixture of Retrieval-augmented multimodal Experts), a novel framework designed to enhance short video hate detection.

[Paper] [Code]

Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning
Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning

Rongpei Hong, Jian Lang, Jin Xu, Zhangtao Cheng, Ting Zhong, Fan Zhou

The Web Conference (WWW) 2025 CCF-A Full Paper

In this work, we introduce ExMRD, a novel Explainable Micro-video Rumor Detection (MVRD) framework designed to generate detailed and coherent explanations for enhancing MVRD.

[Paper] [Code]

Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning

Rongpei Hong, Jian Lang, Jin Xu, Zhangtao Cheng, Ting Zhong, Fan Zhou

The Web Conference (WWW) 2025 CCF-A Full Paper

In this work, we introduce ExMRD, a novel Explainable Micro-video Rumor Detection (MVRD) framework designed to generate detailed and coherent explanations for enhancing MVRD.

[Paper] [Code]

2024

Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning
Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning

Jian Lang*, Zhangtao Cheng*, Jin Xu, Xovee Xu, Yili Li, Fan Zhou (* equal contribution)

The Association for the Advancement of Artificial Intelligence (AAAI) 2025 CCF-A Full Paper

We propose RAGPT, a novel Retrieval-AuGmented dynamic Prompt Tuning framework for enhancing the robustness of pre-trained Multimodal Transformer under modality missing conditions.

[Paper] [Code]

Retrieval-Augmented Dynamic Prompt Tuning for Incomplete Multimodal Learning

Jian Lang*, Zhangtao Cheng*, Jin Xu, Xovee Xu, Yili Li, Fan Zhou (* equal contribution)

The Association for the Advancement of Artificial Intelligence (AAAI) 2025 CCF-A Full Paper

We propose RAGPT, a novel Retrieval-AuGmented dynamic Prompt Tuning framework for enhancing the robustness of pre-trained Multimodal Transformer under modality missing conditions.

[Paper] [Code]

In-context Prompt-augmented Micro-video Popularity Prediction
In-context Prompt-augmented Micro-video Popularity Prediction

Zhangtao Cheng, Jiao Li, Jian Lang, Ting Zhong, Fan Zhou

The Association for the Advancement of Artificial Intelligence (AAAI) 2025 CCF-A Full Paper

Inspired by prompt learning, we propose ICPF, a novel In-Context Prompt-augmented Framework to enhance popularity prediction.

[Paper] [Code]

In-context Prompt-augmented Micro-video Popularity Prediction

Zhangtao Cheng, Jiao Li, Jian Lang, Ting Zhong, Fan Zhou

The Association for the Advancement of Artificial Intelligence (AAAI) 2025 CCF-A Full Paper

Inspired by prompt learning, we propose ICPF, a novel In-Context Prompt-augmented Framework to enhance popularity prediction.

[Paper] [Code]

Seeing the Unseen in Micro-Video Popularity Prediction: Self-Correlation Retrieval for Missing Modality Generation
Seeing the Unseen in Micro-Video Popularity Prediction: Self-Correlation Retrieval for Missing Modality Generation

Zhangtao Cheng*, Jian Lang*, Ting Zhong, Fan Zhou (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 CCF-A Full Paper

We propose SCRAG, a novel Self-Correlation Retrieval-Augmented Generative framework designed to enhance missing-modality robustness in micro-video popularity prediction.

[Paper] [Code]

Seeing the Unseen in Micro-Video Popularity Prediction: Self-Correlation Retrieval for Missing Modality Generation

Zhangtao Cheng*, Jian Lang*, Ting Zhong, Fan Zhou (* equal contribution)

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025 CCF-A Full Paper

We propose SCRAG, a novel Self-Correlation Retrieval-Augmented Generative framework designed to enhance missing-modality robustness in micro-video popularity prediction.

[Paper] [Code]

Predicting Micro-video Popularity via Multi-modal Retrieval Augmentation
Predicting Micro-video Popularity via Multi-modal Retrieval Augmentation

Ting Zhong, Jian Lang, Yifan Zhang, Zhangtao Cheng, Kunpeng Zhang, Fan Zhou

Special Interest Group on Information Retrieval (SIGIR) 2024 CCF-A Short Paper

We present MMRA, a multi-modal retrieval-augmented popularity prediction model that enhances prediction accuracy using relevant retrieved information.

[Paper] [Code]

Predicting Micro-video Popularity via Multi-modal Retrieval Augmentation

Ting Zhong, Jian Lang, Yifan Zhang, Zhangtao Cheng, Kunpeng Zhang, Fan Zhou

Special Interest Group on Information Retrieval (SIGIR) 2024 CCF-A Short Paper

We present MMRA, a multi-modal retrieval-augmented popularity prediction model that enhances prediction accuracy using relevant retrieved information.

[Paper] [Code]