Prentice Hall Interview with Rich Stevens, Author of Unix Programming (1997)
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๐Ÿ“‹Protocol Design
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Stop vibe coding your unit tests
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โœ…Property Testing
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Balancing Cost, Power, and AI Performance
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๐Ÿš€Performance
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Pint: Python library that makes units easy
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๐ŸPython
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Low-Level Hacks
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๐Ÿฆ€Rust
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GMoPE:A Prompt-Expert Mixture Framework for Graph Foundation Models
arxiv.orgยท7h
๐Ÿ’ฌPrompt Engineering
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MemSearcher: Training LLMs to Reason, Search and Manage Memory via End-to-End Reinforcement Learning
arxiv.orgยท1d
๐Ÿ’ฌPrompt Engineering
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LA-MARRVEL: A Knowledge-Grounded and Language-Aware LLM Reranker for AI-MARRVEL in Rare Disease Diagnosis
arxiv.orgยท1d
๐Ÿš€MLOps
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Variational Geometric Information Bottleneck: Learning the Shape of Understanding
arxiv.orgยท1d
๐ŸงฎEmbeddings
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OpenSIR: Open-Ended Self-Improving Reasoner
arxiv.orgยท2d
๐ŸงฎSMT Solvers
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Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat
arxiv.orgยท7h
๐Ÿ’ฌPrompt Engineering
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Deep Value Benchmark: Measuring Whether Models Generalize Deep values or Shallow Preferences
arxiv.orgยท1d
๐Ÿ“ฑEdge AI
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A new language for COBOL workloads, built on GO!
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๐Ÿนgolang
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The Orchestrator Pattern: Routing Conversations to Specialized AI Agents
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๐Ÿ’ฌPrompt Engineering
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Programming Languages Lie: Variables Arenโ€™t What You Think They Are
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๐Ÿ”ฌStatic Analysis
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Decoupled Entropy Minimization
arxiv.orgยท7h
๐Ÿ“ŠInformation Theory
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AI That Shows Its Work: The Transparent Revolution of PALs
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๐ŸŽญProgram Synthesis
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Natural Building Blocks for Structured World Models: Theory, Evidence, and Scaling
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๐Ÿ”€Procedural Generation
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About AI and context
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๐Ÿ’ฌPrompt Engineering
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[D] Trajectory Distillation for Foundation Models
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๐Ÿ’ฌPrompt Engineering
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