An OCC Idea
lambdacreate.com·1d
🗄️Database Internals
Prepare for non-human visitors!
techradar.com·2h
🌀Brotli Internals
June 25, 2025 Flight Tracking Workshop (4 hour) [Americas / Europe-friendly time]
bellingcat.com·2d
🧮Prolog Parsing
Ask HN: Feedback on "QSS" – A Quantized Vector Search Engine in C
news.ycombinator.com·3d·
Discuss: Hacker News
🗂️Vector Databases
Entelligence vs CodeRabbit
dev.to·11h·
Discuss: DEV
🌳Incremental Parsing
LLMs for Customized Marketing Content Generation and Evaluation at Scale
arxiv.org·2d
📊Feed Optimization
MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis
arxiv.org·2d
📊Learned Metrics
CmFNet: Cross-modal Fusion Network for Weakly-supervised Segmentation of Medical Images
arxiv.org·2d
🌀Hyperbolic Geometry
OpenEvents V1: Large-Scale Benchmark Dataset for Multimodal Event Grounding
arxiv.org·2d
📊Learned Metrics
Context Consistency Learning via Sentence Removal for Semi-Supervised Video Paragraph Grounding
arxiv.org·2d
📄Text Chunking
Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
arxiv.org·20h
🤖Advanced OCR
Unfolding the Past: A Comprehensive Deep Learning Approach to Analyzing Incunabula Pages
arxiv.org·2d
🤖Manuscript AI
Agentic Search for Dummies
benanderson.work·4d·
Discuss: Hacker News
🔍Information Retrieval
ColumnTransformer and Pipelines in Scikit-Learn: Clean, Scalable, and Powerful Preprocessing
dev.to·5h·
Discuss: DEV
🌊Streaming Compression
Why Robots Are Bad at Detecting Their Mistakes: Limitations of Miscommunication Detection in Human-Robot Dialogue
arxiv.org·20h
🧠Intelligence Compression
Kafka Fundamentals: kafka retention.ms
dev.to·1d·
Discuss: DEV
🌊Streaming Systems
ReCode: Updating Code API Knowledge with Reinforcement Learning
arxiv.org·20h
⚡Incremental Computation
LARP: Learner-Agnostic Robust Data Prefiltering
arxiv.org·20h
💻Local LLMs
Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration
arxiv.org·20h
👁️OCR Enhancement
Define-ML: An Approach to Ideate Machine Learning-Enabled Systems
arxiv.org·20h
🧠Machine Learning