🎯 Retrieval Systems - matmat · Scour

Natural language processing for word sense disambiguation and information extraction

arxiv.org·17h·

Discuss: r/compsci

📥Feed Aggregation

kalolad1/llm-sorter: A Python library that uses LLMs as comparators for semantic sorting. Sort any list by meaning, tone, complexity, urgency, or any criteria expressible in natural language.

github.com·10h·

Discuss: Hacker News

🔄Burrows-Wheeler

I Built a Video Search Engine That Understands What You're Looking For

dev.to·1d·

Discuss: DEV

🎞️MKV Forensics

Why MAP and MRR Fail for Search Ranking (and What to Use Instead)

towardsdatascience.com·2d

📊Search Ranking

Soft Filtering: Guiding Zero-shot Composed Image Retrieval with Prescriptive and Proscriptive Constraints

arxiv.org·2d

🧮Vector Embeddings

Running Code and Failing Models – Rajiv Shah

projects.rajivshah.com·1d

🧠Machine Learning

The Transformer Architecture: A Deep Dive into How LLMs Actually Work

dev.to·6h·

Discuss: DEV

📝Text Parsing

Document search using Claude and an inverted index.

annanay.dev·5d·

Discuss: Hacker News

🗂️Vector Databases

Retrieval-Augmented Generation for Large Language Models: A Survey

paperium.net·6d·

Discuss: DEV

🌀Brotli Internals

Signal, Noise, and Burnout: A Human-Information Interaction Analysis of Voter Verification in a High-Volatility Environment

arxiv.org·2d

🧭Content Discovery

3 Smart Ways to Encode Categorical Features for Machine Learning - MachineLearningMastery.com

machinelearningmastery.com·5d

🧠Machine Learning

Stanford CS 224N | Natural Language Processing with Deep Learning

web.stanford.edu·1d

🧠Machine Learning

Climate Monitoring Search Engine: Multi-Vectors in Qdrant

pub.towardsai.net

·4d

🗂️Vector Search

MMSRARec: Summarization and Retrieval Augumented Sequential Recommendation Based on Multimodal Large Language Model

arxiv.org·2d

🔍Information Retrieval

CatBoost: gradient boosting with categorical features support

dev.to·1d·

Discuss: DEV

🔍Information Retrieval

Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies: This repository contains a curated collection of 300+ case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are organized to help you easily find relevant case studies based on industry or specific ML use cases.

github.com·4d

🧭Content Discovery

Attention from First Principles

metaworld.me·3d·

Discuss: Lobsters, Hacker News

🧠Machine Learning

Uncovering Competency Gaps in Large Language Models and Their Benchmarks

arxiv.org·2d

⚙️Compression Benchmarking

🧠 Beyond Chatbots: Building 'Echo-Learn', an Agentic AI Tutor with Biological Memory

dev.to·1d·

Discuss: DEV

aashirpersonal/semantic-coverage: Automated detection of knowledge gaps and blind spots in RAG vector stores.

github.com·3d·

Discuss: Hacker News

🌀Brotli Internals

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