Participate in the Digital Preservation Bake Off (Tools Demonstration) at iPRES 2025
dpconline.org·1d
📄Document Digitization
Apple Just Patented an Image Sensor with 20 Stops of Dynamic Range
ymcinema.com·18h·
Discuss: Hacker News
🖼️JPEG XL
The AI Arms Race: When Attackers Leverage Cutting-Edge Tech
blog.checkpoint.com·1d
🕵️Vector Smuggling
Normalizing Flows are Capable Generative Models
machinelearning.apple.com·1d·
Discuss: Hacker News
🧠Learned Compression
🚀 Kickstart Your PL-300 Journey with Practice Lab 1!
dev.to·19h·
Discuss: DEV
🧠Query Planners
Semantic-Aware Parsing for Security Logs
arxiv.org·3d
📝Log Parsing
Show HN: 10x Kubernetes Cluster on Hetzner Cloud
github.com·16h·
Discuss: Hacker News
📦Container Security
From Vibe Coding to Vibe Videoing: How AI is Democratizing Creative Production
dev.to·2d·
Discuss: DEV
💿Binary Musicology
How Keploy Transformed My API Testing Experience During Their Fellowship Program
dev.to·19h·
Discuss: DEV
🔍Concolic Testing
Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettes
arxiv.org·20h
🧠Intelligence Compression
How to Learn AI for Data Analytics in 2025
kdnuggets.com·12h
🤖Archive Automation
Unveiling the Magic of Variational Autoencoders: Learning to Generate from Data
dev.to·1d·
Discuss: DEV
🧠Neural Compression
Fully lifted \emph{blirp} interpolation -- a large deviation view
arxiv.org·2d
🌀Fractal Compression
ReMAR-DS: Recalibrated Feature Learning for Metal Artifact Reduction and CT Domain Transformation
arxiv.org·2d
📊Learned Metrics
GLIMPSE: Gradient-Layer Importance Mapping for Prompted Visual Saliency Explanation for Generative LVLMs
arxiv.org·2d
📊Learned Metrics
Lightweight Target-Speaker-Based Overlap Transcription for Practical Streaming ASR
arxiv.org·1d
🎙️Whisper
Structural System Identification via Validation and Adaptation
arxiv.org·20h
🧠Machine Learning
Hong Mong 5 Development Treasure Case Sharing Buried Point Development Real Battle Guide
dev.to·2d·
Discuss: DEV
🔗Data Provenance
Machine Learning Fundamentals: active learning project
dev.to·2d·
Discuss: DEV
🧠Machine Learning
Kernel spectral joint embeddings for high-dimensional noisy datasets using duo-landmark integral operators
arxiv.org·3d
🌀Riemannian Computing