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📰 SGML
Have Yourself a One Page Dungeon
virtualmoose.org·17h
📏Linear Logic
Thinking Thursday: Paul Lockhart
denisegaskins.com·17h
🔬Lean
Copilot Features That Felt Like Magic
iamvishnu.com·3d
🖥️Modern Terminals
Cocoindex: Data Transformation for AI
cocoindex.io·12h·
Discuss: Hacker News
⚙️Batch Processing
LLMs are telepathy. We just don't know it yet
monarchwadia.com·1h·
Discuss: Hacker News
🏛Digital humanities
Intermediate and Advanced K8S CRDs and Operators Interview Questions
reddit.com·1d·
Discuss: r/kubernetes
🔗Constraint Handling
BREAKING NEWS: AI coding may not be helping as much as you think
garymarcus.substack.com·12h·
Discuss: Substack
📏Code Metrics
[D] How to avoid feature re-coding?
reddit.com·11h·
Discuss: r/MachineLearning
🌊Streaming Systems
ViTaL: A Multimodality Dataset and Benchmark for Multi-pathological Ovarian Tumor Recognition
arxiv.org·3d
🧠Machine Learning
Comparative Analysis of CNN and Transformer Architectures with Heart Cycle Normalization for Automated Phonocardiogram Classification
arxiv.org·1d
🎵Audio ML
Machine Bullshit: Characterizing the Emergent Disregard for Truth in Large Language Models
arxiv.org·2h
⚡Proof Automation
A beginner's guide to the Flux-Kontext-Pro model by Black-Forest-Labs on Replicate
dev.to·14h·
Discuss: DEV
🎙️Whisper
Adversarial Defenses via Vector Quantization
arxiv.org·2h
📊Vector Quantization
Show HN: I built tinyORM, a minimal, database-agnostic TypeScript ORM
github.com·2d·
Discuss: Hacker News
🎯Dependent Preservation
Replace AI References in Comments with Tests That Actually Work
hackernoon.com·4d
⚡Proof Automation
Lack of evidence for the transitional cerebellar progenitor
nature.com·1d
🧬Copy Number Variants
Reinforcement Learning with Action Chunking
arxiv.org·2h
🔲Cellular Automata
ChestGPT: Integrating Large Language Models and Vision Transformers for Disease Detection and Localization in Chest X-Rays
arxiv.org·3d
🏛Digital humanities
Causal-SAM-LLM: Large Language Models as Causal Reasoners for Robust Medical Segmentation
arxiv.org·3d
🧠Machine Learning
KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
arxiv.org·1d
🧠Machine Learning
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