5 citations · 5 across the 3 of their papers we have counts for
9 papers
Reasoning-Aware Multimodal Fusion for Hateful Video Detection
Shuonan Yang, Tailin Chen, Jiangbei Yue +3
Hate speech in online videos is posing an increasingly serious threat to digital platforms, especially as video content becomes increasingly multimodal and context-dependent. Exist…
Safe Multi-Agent Behavior Must Be Maintained, Not Merely Asserted: Constraint Drift in LLM-Based Multi-Agent Systems
Tianxiao Li, Yixing Ma, Haiquan Wen +4
Modern LLM based agents are no longer passive text generators. They read repositories, call tools, browse the web, execute code, maintain memory, communicate with other agents, and…
Omni-Fake: Benchmarking Unified Multimodal Social Media Deepfake Detection
Tianxiao Li, Zhenglin Huang, Haiquan Wen +10
Multimodal deepfakes are proliferating on social media and threaten authenticity, information integrity, and digital forensics. Existing benchmarks are constrained by their single-…
Towards Training-free Multimodal Hate Localisation with Large Language Models
Yueming Sun, Long Yang, Jianbo Jiao +1
The proliferation of hateful content in online videos poses severe threats to individual well-being and societal harmony. However, existing solutions for video hate detection eithe…
MultiHateLoc: Towards Temporal Localisation of Multimodal Hate Content in Online Videos
Qiyue Sun, Tailin Chen, Yinghui Zhang +4
The rapid growth of video content on platforms such as TikTok and YouTube has intensified the spread of multimodal hate speech, where harmful cues emerge subtly and asynchronously…
Training-Free and Interpretable Hateful Video Detection via Multi-stage Adversarial Reasoning
Shuonan Yang, Yuchen Zhang, Zeyu Fu
Hateful videos pose serious risks by amplifying discrimination, inciting violence, and undermining online safety. Existing training-based hateful video detection methods are constr…