Linkage
11011110.github.io·6d
🔍AI Detection
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Building Software That Survives • Michael Nygard & Charles Humble • GOTO 2025
youtube.com·3d
🌐Open Source
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Understanding Federated Learning: Best Practices for Implementing Privacy-Preserving AI in C# Projects
⚡DataFusion
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[P] triplet-extract: GPU-accelerated triplet extraction via Stanford OpenIE in pure Python
🐻Polars
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Feature Stores 2.0: The Next Frontier of Scalable Data Engineering for AI
hackernoon.com·2d
🏗data engineering
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Large Language Models as Information Sources: Distinctive Characteristics and Types of Low-Quality Information
arxiv.org·1d
🔄Feed Aggregation
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Multi-Modal Feature Fusion for Spatial Morphology Analysis of Traditional Villages via Hierarchical Graph Neural Networks
arxiv.org·4d
🕸️Graph Databases
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OpenSIR: Open-Ended Self-Improving Reasoner
arxiv.org·3d
⚙️Query Compilers
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Trust in the Machine: Building Reputable Service Networks for AI Agents
🎮Reinforcement Learning
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Building a Self-Improving RAG System with Smart Query Routing and Answer Validation
🧮Apache Calcite
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The Design Innovations of NopGraphQL: From API Protocol to a General-Purpose Information Operation Engine
⚡DataFusion
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Automated Multi-Modal Knowledge Graph Scoring for Cohort-Based Retrospective Analytics
🔍AI Detection
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Hypergraph Embedding Optimization for Graph Database Query Acceleration via Differential Evolution
🕸️Graph Databases
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GMoPE:A Prompt-Expert Mixture Framework for Graph Foundation Models
arxiv.org·1d
🕸️Graph Databases
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Biological Regulatory Network Inference through Circular Causal Structure Learning
arxiv.org·2d
🧬Quantum Biology
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Detailed Technical Documentation on AI Implementation Logic (Taking Large Language Models as an Example )
⚙️Query Compilers
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"Let's Agree to Disagree": Investigating the Disagreement Problem in Explainable AI for Text Summarization
arxiv.org·55m
🔄Feed Aggregation
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Reasoning models don't degrade gracefully - they hit a complexity cliff and collapse entirely [Research Analysis] [R]
🏗data engineering
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