Author: Aubrey Price

Authors: Akriti Verma、Shama Islam、Valeh Moghaddam、Adnan Anwar、Sharon Horwood Paper: https://arxiv.org/abs/2408.07704 Introduction In today’s digital age, social media platforms like Facebook, Twitter, Reddit, and Instagram have become integral to our daily lives. These platforms serve as avenues for sharing emotions and seeking emotional support, thus playing a crucial role in managing people’s emotions. However, these platforms are not specifically designed for emotion regulation, which limits their effectiveness. This paper proposes an innovative approach to enhance Interpersonal Emotion Regulation (IER) on online platforms through content recommendation. The goal is to empower users to regulate their emotions by recommending media content that aligns with…

Authors: Jun Yuan、Aritra Dasgupta Paper: https://arxiv.org/abs/2408.06509 Introduction Explainable AI (XAI) methods, such as SHAP, are crucial for uncovering feature attributions in black-box models. These methods help identify if a model’s predictions are influenced by “protected features” like gender or race, which can indicate unfairness. However, adversarial attacks can undermine the effectiveness of these XAI methods. This paper introduces a novel family of data-agnostic attacks called shuffling attacks, which can adapt any trained machine learning model to fool Shapley value-based explanations. The authors demonstrate that Shapley values cannot detect these attacks, though algorithms estimating Shapley values, such as linear SHAP and…

Authors: Matthias Bartolo、Dylan Seychell、Josef Bajada Paper: https://arxiv.org/abs/2408.06803 Introduction Object detection is a fundamental problem in computer vision, involving the identification and localization of objects within images or videos. Despite significant advancements, challenges remain due to the variability in object appearance, occlusion, and lighting conditions. This study explores the integration of reinforcement learning (RL) and saliency ranking techniques to enhance object detection accuracy. By leveraging saliency ranking for initial bounding box prediction and refining these predictions using RL, the study aims to develop faster and more optimized models. Background Saliency Ranking Saliency ranking identifies the most visually significant features within an…