CybAI news

arXiv:2411.14565v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anomalous events that may cause harm without physical contact. However, vision-based surveillance systems such as closed-circuit television often capture personally identifiable information. The lack of transparency and interpretability in video transmission and usage raises public concerns about privacy and ethics, limiting the real-world application of VAD. Recently, researchers have focused on privacy concerns in VAD by conducting systematic studies from various perspectives including data, features, and systems, making Privacy-Preserving Video Anomaly Detection (P2VAD) a hotspot in…

[Submitted on 9 May 2024 (v1), last revised 21 Nov 2024 (this version, v2)] View a PDF of the paper titled Large Language Models Show Human-like Social Desirability Biases in Survey Responses, by Aadesh Salecha and 5 other authors View PDF HTML (experimental) Abstract:As Large Language Models (LLMs) become widely used to model and simulate human behavior, understanding their biases becomes critical. We developed an experimental framework using Big Five personality surveys and uncovered a previously undetected social desirability bias in a wide range of LLMs. By systematically varying the number of questions LLMs were exposed to, we demonstrate their…