Bullying Is Not Innovation
🤖AI Curation
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Quantum-Resistant Federated Learning: Implementing Post-Quantum Cryptography in Cross-Silo Model Aggregation
🔐Quantum Security
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Casing Collar Identification using AlexNet-based Neural Networks for Depth Measurement in Oil and Gas Wells
arxiv.org·23h
🧠Machine Learning
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A Multimodal Dataset for Indoor Radio Mapping with 3D Point Clouds and RSSI
arxiv.org·23h
📻Homebrew Protocols
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A Retrospect to Multi-prompt Learning across Vision and Language
arxiv.org·23h
📊Learned Metrics
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MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electrocardiogram Data
arxiv.org·1d
🎵Audio ML
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Reevaluating Self-Consistency Scaling in Multi-Agent Systems
arxiv.org·23h
🔲Cellular Automata
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Advancing Cognitive Science with LLMs
arxiv.org·23h
🧠Intelligence Compression
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Gen AI in Automotive: Applications, Challenges, and Opportunities with a Case study on In-Vehicle Experience
arxiv.org·23h
🎙️Whisper
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HUME: Measuring the Human-Model Performance Gap in Text Embedding Task
🧠Intelligence Compression
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DocPrism: Local Categorization and External Filtering to Identify Relevant Code-Documentation Inconsistencies
arxiv.org·23h
🎯Gradual Typing
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Algorithmic Alchemy: Transmuting Dynamic Programming with Gradients by Arvind Sundararajan
🎯Performance Proofs
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Text-guided Fine-Grained Video Anomaly Detection
arxiv.org·23h
🤖Advanced OCR
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Automated Anomaly Detection and Predictive Maintenance in Self-Propelled Brush Rollers Using Bayesian Network Fusion
🌊Stream Processing
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EVINGCA: Adaptive Graph Clustering with Evolving Neighborhood Statistics
arxiv.org·23h
🌊Spectral Clustering
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A Hybrid Deep Learning and Forensic Approach for Robust Deepfake Detection
arxiv.org·1d
🔍Vector Forensics
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Building Syllabi – Agentic AI with Vercel AI SDK, Dynamic Tool Loading, and RAG
⚡Proof Automation
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Towards Reliable Pediatric Brain Tumor Segmentation: Task-Specific nnU-Net Enhancements
arxiv.org·23h
🗂️Vector Databases
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Dialogue as Discovery: Navigating Human Intent Through Principled Inquiry
arxiv.org·1d
🧭Content Discovery
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