Preventing AI Project Failures Through Effective Prompt Engineering
dev.to·5h·
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MoM: Mixtures of Scenario-Aware Document Memories for Retrieval-AugmentedGeneration Systems
paperium.net·2d·
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Tokens: The Invisible Building Blocks of Large Language Models
dev.to·5h·
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AI Isn't Alchemy: Not Mystical, Just Messy
craftedlogiclab.com·20m·
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DialectGen: Benchmarking and Improving Dialect Robustness in MultimodalGeneration
dev.to·1d·
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PolyNorm: Few-Shot LLM-Based Text Normalization for Text-to-Speech
machinelearning.apple.com·3d
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**Practical Tip: Fine-Tuning LLMs for Improved Generalizabil
dev.to·21h·
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Book review: “Build a DeepSeek Model (From Scratch)”
dev.to·1d·
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AI tech can compress LLM chatbot conversation memory by 3–4 times
techxplore.com·2d
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Epidemiology of Large Language Models: A Benchmark for Observational Distribution Knowledge
arxiv.org·3d
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Continuous Autoregressive Language Models
shaochenze.github.io·4d·
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How to Use GPT-5 Effectively
towardsdatascience.com·2d
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Benchmark for Agent Context Engineering (2025)
tarasyarema.com·3h·
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Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection toDiffusion Language Models
paperium.net·1d·
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Explore to Evolve: Scaling Evolved Aggregation Logic via Proactive OnlineExploration for Deep Research Agents
dev.to·7h·
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GPTF-8: A tokenizer-based character encoding
lesswrong.com·2d
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Forget the Math: A Beginner’s Guide to How Attention Powers GPT and Transformers
pub.towardsai.net·10h
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7 unusual programming languages that are worth taking a look at
howtogeek.com·29m
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AI Assisted Website Navigation
willvincentparrone.com·3h·
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50 % smaller LLM same PPL, experimental architecture
reddit.com·1d·
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