Post-training methods for language models
developers.redhat.com·5d
💬Prompt Engineering
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How Small Teams Can Scale Global Content Without Hiring a Translation Agency
💬Natural Language Processing
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Ruby and Its Neighbors: Smalltalk
💎Refinement Types
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Beyond Standard LLMs
🤖Transformers
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Show HN: XML-Lib – An over-engineered XML workflow with guardrails and proofs
📚Technical Writing
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DialectalArabicMMLU: Benchmarking Dialectal Capabilities in Arabic and Multilingual Language Models
arxiv.org·6d
🦙Ollama
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MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal MathematicalReasoning
🧮SMT Solvers
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LiveResearchBench: A Live Benchmark for User-Centric Deep Research in the Wild
🚀Performance
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A Systematic Literature Review of Code Hallucinations in LLMs: Characterization, Mitigation Methods, Challenges, and Future Directions for Reliable AI
arxiv.org·5d
⚙️JIT Compilation
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Beyond the App
💬Prompt Engineering
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AI Coding Assistants: Boon or Bane?
🎭Program Synthesis
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