Paper2Web: Let's Make Your Paper Alive
📄PostScript
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Using Claude Skills with Neo4j
towardsdatascience.com·4h
🕸️Neo4j
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NeuroPilot: A Realtime Brain-Computer Interface system to enhance concentration of students in online learning
arxiv.org·1d
🎯Threat Hunting
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Supervised Fine-Tuning or In-Context Learning? Evaluating LLMs for Clinical NER
arxiv.org·18h
⚙️Compression Benchmarking
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"Go-ing" Crazy? Why This Little Gopher is Your New Best Friend ! 🚀
🔗Concatenative Programming
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ConMatFormer: A Multi-attention and Transformer Integrated ConvNext based Deep Learning Model for Enhanced Diabetic Foot Ulcer Classification
arxiv.org·18h
📊Learned Metrics
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LOC: A General Language-Guided Framework for Open-Set 3D Occupancy Prediction
arxiv.org·18h
🏺Computational Archaeology
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Education Paradigm Shift To Maintain Human Competitive Advantage Over AI
arxiv.org·18h
🔲Cellular Automata
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A beginner's guide to the Video-Utils model by Nicolascoutureau on Replicate
🎬Video Codecs
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Improved Training Technique for Shortcut Models
arxiv.org·1d
📊Learned Metrics
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Accelerating Data Generation for Nonlinear temporal PDEs via homologous perturbation in solution space
arxiv.org·1d
🌀Differential Geometry
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SindBERT, the Sailor: Charting the Seas of Turkish NLP
arxiv.org·1d
📝Text Parsing
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Leverage Unlearning to Sanitize LLMs
arxiv.org·1d
💻Local LLMs
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ROPES: Robotic Pose Estimation via Score-Based Causal Representation Learning
arxiv.org·1d
🌀Riemannian Computing
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VESSA: Video-based objEct-centric Self-Supervised Adaptation for Visual Foundation Models
arxiv.org·1d
📊Learned Metrics
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A Closed-Loop Personalized Learning Agent Integrating Neural Cognitive Diagnosis, Bounded-Ability Adaptive Testing, and LLM-Driven Feedback
arxiv.org·18h
🧠Intelligence Compression
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Estimating the Error of Large Language Models at Pairwise Text Comparison
arxiv.org·18h
🧮Kolmogorov Complexity
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A Flow Model with Low-Rank Transformers for Incomplete Multimodal Survival Analysis
arxiv.org·18h
📐Vector Dimensionality
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Think before Recommendation: Autonomous Reasoning-enhanced Recommender
arxiv.org·18h
🎯Content Recommendation
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