Hyper-Personalized Customer Journey Orchestration via Probabilistic Temporal Logic Modeling in CRM
dev.to·6h·
Discuss: DEV
🎛️Feed Filtering
LLM-Based Instance-Driven Heuristic Bias in the Context of a BRKGA
researchgate.net·19h·
Discuss: Hacker News
🧮Kolmogorov Complexity
Eliminating the Precision–Latency Trade-Off in Large-Scale RAG
thenewstack.io·1d
🎯Retrieval Systems
Contrastive Retrieval Heads Improve Attention-Based Re-Ranking
arxiv.org·2d
🔍Information Retrieval
AI-Driven Personalization Improving Decision-Making and Real-Time Analytics
future.forem.com·2d·
Discuss: DEV
🎛️Feed Filtering
Lazy text capitalization with low latency large language models
blog.florianschulz.info·23h·
Discuss: Hacker News
🌀Brotli Internals
Show HN: I Started the New SEO
spore-ten.vercel.app·13h·
Discuss: Hacker News
📊Feed Optimization
TypeNet Benchmark for development of authentication keystroke technologies
github.com·10h·
Discuss: Hacker News
🗜️LZSS Variants
AI Self-Preferencing in Algorithmic Hiring: Empirical Evidence and Insights
papers.ssrn.com·1d·
Discuss: Hacker News
🌍Cultural Algorithms
Algorithm Showdown: Logistic Regression vs. Random Forest vs. XGBoost on Imbalanced Data
machinelearningmastery.com·2d
🧠Machine Learning
Anatomy of a Modern Finetuning API
benanderson.work·7h·
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💻Local LLMs
Show HN: Got sick and tired of AI in search engines, so I made my own
glass.8ball.space·23h·
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🔍BitFunnel
Prediction vs. Search Models: What Data Scientists Are Missing
towardsdatascience.com·2d
🧪Data science
Comet
perplexity.ai·3h·
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📰Feed Readers
Personalized Reasoning: Just-In-Time Personalization and Why LLMs Fail At It
arxiv.org·3d
🧮Theorem Proving
Show HN: Fast API for Data Cleaning
getflookup.com·1d·
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🔍BitFunnel
Why Google will win the AI race
investinginai.substack.com·2h·
Discuss: Substack
🤖AI Curation
An Overview of Modern Memory Management Architectures in LLM Agents
vinithavn.medium.com·56m·
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💾Persistence Strategies
How to Train an LLM to Do Proofs: Beyond Verifiable Rewards
tobysimonds.com·15h·
Discuss: Hacker News
🎯Interactive Provers
Sparse Query Attention (SQA): A Computationally Efficient Attention Mechanism with Query Heads Reduction
arxiv.org·2d
🔍Information Retrieval