6 accepted papers
Short-video platforms now host vast multimodal ads whose deceptive visuals, speech and subtitles demand finer-grained, policy-driven moderation than community safety filters. We present BLM-Guard, a content-audit framework for commercial ads that fuses Chain-of-Thought reasoning with rule-based poli
In an ideal medical environment, real-time coagulation monitoring can enable early detection and prompt remediation of risks. However, traditional Thromboelastography (TEG), a widely employed diagnostic modality, can only provide such outputs after nearly 1 hour of measurement. The delay might lead
With the commercialization of short video platforms (SVPs), the demand for compliance auditing of advertising content has grown rapidly. The rise of large vision-language models (VLMs) offers new opportunities for automating ad content moderation. However, short video advertising scenarios present u
Emotion recognition in shooting is of great importance for improving athletes’ training methods. However, there is no open and high confident electroencephalography (EEG) dataset about shooting due to the difficulty of data acquisition, which made it a challenge for related studies. In this paper, w…
Estimated time of arrival (ETA) is one of the most important services in intelligent transportation systems (ITS) and becomes a challenging spatial-temporal (ST) data mining task in recent years. Nowadays, deep learning based methods, specifically recurrent neural networks (RNN) based ones are adapt…
Previous works have discovered that general DNNs are vulnerable under some subtle and specific perturbations on classification tasks. In recent years, deep neural networks (DNNs) unfolded through sparse coding algorithms have achieved great success in sparse coding problem. Some applications of spar…