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🧮 Datalog Engines

Soufflé, Bottom-up Evaluation, Recursive Queries, Graph Analysis

Diving deep into Binius M3 arithmetization using Merkle tree inclusion as an example
blog.lambdaclass.com·2d
🌳Archive Merkle Trees
Exploring High Efficiency Web Analysis Results(1750876031390300)
dev.to·7h·
Discuss: DEV
🌊Stream Processing
SUTRA: Decoupling Concept & Language for Multilingual LLM Excellence
hackernoon.com·10h
💻Local LLMs
Is SPL more difficult or easier than SQL?
github.com·18h·
Discuss: Hacker News
⛏️SQL Archaeology
Dual-Hierarchy Labelling: Scaling Up Distance Queries on Dynamic Road Networks
arxiv.org·1d
📏Range Queries
PARALLELPROMPT: Extracting Parallelism from Large Language Model Queries
arxiv.org·1d
🚀SIMD Text Processing
A Briefing on Logistic Regression
blog.engora.com·14h·
Discuss: Hacker News
🧠Machine Learning
Deciding Termination of Simple Randomized Loops
arxiv.org·1d
🌳Persistent Data Structures
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning
arxiv.org·22h
🌀Riemannian Computing
When Data Becomes a Bottleneck: Why Smart People Still Struggle to Get Answers
dev.to·14h·
Discuss: DEV
🌊Stream Processing
Black-Box Test Code Fault Localization Driven by Large Language Models and Execution Estimation
arxiv.org·22h
🔍Concolic Testing
Hidden Complexities of Scaling GraphQL Federation (And How to Fix Them)
dev.to·12h·
Discuss: DEV
📊Graph Databases
Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes
arxiv.org·22h
🔍Type Inference
Scalable Machine Learning Algorithms using Path Signatures
arxiv.org·1d
🧠Machine Learning
A Lisp adventure on the calm waters of the dead C (2021)
mihaiolteanu.me·2d·
Discuss: Lobsters, Hacker News, r/programming
🔗Lisp
Using an LLM for query planning in RAG –> 40% better answer relevance
techcommunity.microsoft.com·1d·
Discuss: Hacker News
🔍Information Retrieval
Flame Graph Performance Truth Analysis(1750839255230100)
dev.to·18h·
Discuss: DEV
⚡Performance Tools
Machine Learning Fundamentals: active learning tutorial
dev.to·10h·
Discuss: DEV
🎛️Feed Filtering
BNFGen: A random text generator based on context-free grammars
baturin.org·8h·
Discuss: Hacker News
🌳Context free grammars
Machine Learning Fundamentals: active learning with python
dev.to·9h·
Discuss: DEV
🧠Machine Learning
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