What Medieval People Got Right About Learning (2019)
scotthyoung.com·1d·
Discuss: Hacker News
Is Meta Scraping the Fediverse for AI?
wedistribute.org·2d·
Discuss: Hacker News
Large Language Models for Oral History Understanding with Text Classification and Sentiment Analysis
arxiv.org·3d
AI Security Map: Holistic Organization of AI Security Technologies and Impacts on Stakeholders
arxiv.org·2d
Chimera: Harnessing Multi-Agent LLMs for Automatic Insider Threat Simulation
arxiv.org·3d
MAQuA: Adaptive Question-Asking for Multidimensional Mental Health Screening using Item Response Theory
arxiv.org·3d
EDGE: A Theoretical Framework for Misconception-Aware Adaptive Learning
arxiv.org·3d
Cross-Subject and Cross-Montage EEG Transfer Learning via Individual Tangent Space Alignment and Spatial-Riemannian Feature Fusion
arxiv.org·3d
An Unsupervised Deep XAI Framework for Localization of Concurrent Replay Attacks in Nuclear Reactor Signals
arxiv.org·1d
Between Fear and Desire, the Monster Artificial Intelligence (AI): Analysis through the Lenses of Monster Theory
arxiv.org·2d
Can Smaller Large Language Models Evaluate Research Quality?
arxiv.org·3d
Federated Online Learning for Heterogeneous Multisource Streaming Data
arxiv.org·3d
Rare AI and the Fermi Paradox
lesswrong.com·12h
MOC: Meta-Optimized Classifier for Few-Shot Whole Slide Image Classification
arxiv.org·1d
GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs
arxiv.org·1d
Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning
arxiv.org·3d
Fuzzy-Pattern Tsetlin Machine
arxiv.org·2d
AI Blob! LLM-Driven Recontextualization of Italian Television Archives
arxiv.org·1d
Strategies of Code-switching in Human-Machine Dialogs
arxiv.org·3d
ViMoNet: A Multimodal Vision-Language Framework for Human Behavior Understanding from Motion and Video
arxiv.org·1d