Broken news: Expert says supply chain thinking could help restore trust in media
phys.org·14h
📡RSS Readers
From ”Need to Know” to ”Need to Share”: Navigating Information Overload and Source Protection in Modern Intelligence
kkrva.se·23h
🇸🇪Swedish Cryptanalysis
From Static Rate Limiting to Adaptive Traffic Management in Airbnb’s Key-Value Store
medium.com·13h
🌊Streaming Systems
A small number of samples can poison LLMs of any size
anthropic.com·13h·
Discuss: Lobsters, Hacker News
🔍Vector Forensics
The key to conversational speech recognition
datasciencecentral.com·11h
🎵Audio ML
Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention
huggingface.co·22h·
Discuss: Hacker News
📊Learned Metrics
I analyzed 70 Data Breaches. Three controls would have stopped 65% of them
securityblueprints.io·12h·
Discuss: Hacker News
🔐Capability Systems
On Convex Functions of Gaussian Variables
arxiv.org·1d
📐Compression Mathematics
Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards
arxiv.org·1h
🧮Theorem Proving
MARC: Memory-Augmented RL Token Compression for Efficient Video Understanding
arxiv.org·1h
🧠Learned Codecs
The Rise of the Knowledge Sculptor: A New Archetype for Knowledge Work in the Age of Generative AI
arxiv.org·1h
🗺️Competency Maps
Sub-Field Selection & Research Topic Generation:
dev.to·8h·
Discuss: DEV
🌀Differential Geometry
Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness
arxiv.org·1d
🧠Intelligence Compression
Recurrent Natural Policy Gradient for POMDPs
arxiv.org·1h
🔲Cellular Automata
Mortality-Driven AI: Building Better Bots by Embracing Limits by Arvind Sundararajan
dev.to·15h·
Discuss: DEV
🔲Cellular Automata
Latency vs. Accuracy for LLM Apps — How to Choose and How a Memory Layer Lets You Win Both
dev.to·2d·
Discuss: DEV
⚡Performance Mythology
ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall
arxiv.org·1h
✨Effect Handlers
SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
arxiv.org·1h
🧠Neural Codecs
Retentive Relevance: Capturing Long-Term User Value in Recommendation Systems
arxiv.org·1h
🎯Content Recommendation
Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
arxiv.org·3d
🧠Machine Learning