original ↗
raymondcamden.com·18h
🦀Rust
Database.news – curated list of database news from authoritative sources
database.news·3d·
Discuss: Lobsters, Hacker News
🗄️Database Theory
Wait Don't spawn that task – Comparing patterns for mutable state
taping-memory.dev·1d·
Discuss: Hacker News, Hacker News, r/programming
⚡Concurrency
The "high-level CPU" challenge
yosefk.com·2d·
Discuss: Lobsters, Hacker News, Hacker News
🏗Computer Architecture
The AI Was Fed Sloppy Code. It Turned Into Something Evil.
quantamagazine.org·1d·
Discuss: Hacker News
🤖Sci-Fi
How Graphs Boost LLM Precision and Explainability in Cybersecurity
hackernoon.com·3d
🧭SMT Solvers
Ambient Intelligence from a Bird? You Won’t Believe What This Code Does
dev.to·4h·
Discuss: DEV
🧮Programming Language Theory
Daily JavaScript Challenge #JS-251: Calculate Sum of Prime Numbers Below a Given Number
dev.to·18h·
Discuss: DEV
🧩Theorem Proving
A Context-aware Attention and Graph Neural Network-based Multimodal Framework for Misogyny Detection
arxiv.org·14h
🕸️Graph Theory
dolthub/dolt v1.58.3
github.com·1d
🦀Rust
Chi-Geometry: A Library for Benchmarking Chirality Prediction of GNNs
arxiv.org·1d
🕸️Graph Theory
Pareto Multi-Objective Alignment for Language Models
arxiv.org·2d
🔗Parser Combinators
impuTMAE: Multi-modal Transformer with Masked Pre-training for Missing Modalities Imputation in Cancer Survival Prediction
arxiv.org·14h
🎲Probabilistic Programming
A Risk Taxonomy and Reflection Tool for Large Language Model Adoption in Public Health
arxiv.org·1d
🎲Probabilistic Programming
Hallucination vs interpretation: rethinking accuracy and precision in AI-assisted data extraction for knowledge synthesis
arxiv.org·14h
🔗Parser Combinators
HTTP Request Processing with Zero-Copy Optimization(0979)
dev.to·1d·
Discuss: DEV
🤝Protocol Design
The best explanation of LLMs I've ever seen is in this new book.
threadreaderapp.com·2d
🔗Parser Combinators
Unlocking Scalability: A Deep Dive into Mixture of Experts (MoE) for Modern LLMs
dev.to·2d·
Discuss: DEV
🎲Probabilistic Programming
Building ML Infrastructure in TypeScript - Part 1: The Vision
dev.to·1d·
Discuss: DEV
🧮Programming Language Theory
LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference
arxiv.org·2d
🎲Probabilistic Programming