To enhance the accuracy and efficiency of mining grassroots network data and to better support practical applications, this study proposes a personalized mining algorithm for grassroots network data based on deep learning. A multi-module neural network architecture is designed to process, filter, and transform raw grassroots network data. Through data preprocessing and hierarchical refinement, the algorithm generates high-precision, structured datasets suitable for personalized mining tasks. A five-layer neural network-comprising an input layer, convolutional input layer, hidden layer, convolutional […]

Ver mais

arXiv:2601.00240v1 Announce Type: new Abstract: LLM-empowered agents can exhibit not only demographic bias (e.g., gender, religion) but also intergroup bias triggered by minimal “us” versus “them” cues. When this intergroup boundary aligns with an agent-human divide, the risk shifts from disparities among human demographic groups to a more fundamental group-level asymmetry, i.e., humans as a whole may be treated as the outgroup by agents. To examine this possibility, we construct a controlled multi-agent social simulation based on allocation […]

Ver mais

Mobile Software Engineering has emerged as a distinct subfield, raising questions about the transferability of its research findings to general Software Engineering. This paper addresses the challenge of evaluating the generalizability of mobile-specific research, using Green Computing as a representative case. We propose a systematic method that combines a mapping study to identify potentially overlooked mobile-specific papers with a focused literature review to assess their broader relevance. Applying this approach, we find that several mobile-specific studies offer insights […]

Ver mais

arXiv:2601.04352v1 Announce Type: new Abstract: This study presents a comprehensive comparative analysis of custom-built Convolutional Neural Networks (CNNs) against popular pre-trained architectures (ResNet-18 and VGG-16) using both feature extraction and transfer learning approaches. We evaluated these models across five diverse image classification datasets from Bangladesh: Footpath Vision, Auto Rickshaw Detection, Mango Image Classification, Paddy Variety Recognition, and Road Damage Detection. Our experimental results demonstrate that transfer learning with fine-tuning consistently outperforms both custom CNNs built from scratch and […]

Ver mais

Meta researchers have introduced Perception Encoder Audiovisual, PEAV, as a new family of encoders for joint audio and video understanding. The model learns aligned audio, video, and text representations in a single embedding space using large scale contrastive training on about 100M audio video pairs with text captions. From Perception Encoder to PEAV Perception Encoder, PE, is the core vision stack in Meta’s Perception Models project. It is a family of encoders for images, video, and audio that […]

Ver mais

arXiv:2601.03326v1 Announce Type: new Abstract: PCA can be used for rotation invariant features, describing a shape with its $p_{ab}=E[(x_i-E[x_a])(x_b-E[x_b])]$ covariance matrix approximating shape by ellipsoid, allowing for rotation invariants like its traces of powers. However, real shapes are usually much more complicated, hence there is proposed its extension to e.g. $p_{abc}=E[(x_a-E[x_a])(x_b-E[x_b])(x_c-E[x_c])]$ order-3 or higher tensors describing central moments, or polynomial times Gaussian allowing decodable shape descriptors of arbitrarily high accuracy, and their analogous rotation invariants. Its practical applications […]

Ver mais

Large Language Model (LLM)-based agents have fundamentally reshaped artificial intelligence by integrating external tools and planning capabilities. While memory mechanisms have emerged as the architectural cornerstone of these systems, current research remains fragmented, oscillating between operating system engineering and cognitive science. This theoretical divide prevents a unified view of technological synthesis and a coherent evolutionary perspective. To bridge this gap, this survey proposes a novel evolutionary framework for LLM agent memory mechanisms, formalizing the development process into three […]

Ver mais

Key Highlights: Reddit has overtaken TikTok to become the UK’s fourth most visited social media platform, as changes in search algorithms and shifting Gen Z behaviour push users toward discussion-based content over short-form video. Reddit Overtakes TikTok in the UK as Search Algorithms and Gen Z Habits Drive Growth The online forum platform has experienced rapid growth over the past two years, with the share of UK internet users who encounter Reddit increasing by 88%, according to data […]

Ver mais