✨ LLMs - hop1.ng.1357 · Scour

Can Large Language Models Reinvent Foundational Algorithms? 🤖LLM

arxiv.org·2d

LLM inference engine from scratch in C++ 🤖LLM

anirudhsathiya.com·4d·Hacker News

milanm/AutoGrad-Engine: A complete GPT language model (training and inference) in ~600 lines of pure C#, zero dependencies 🤖LLM

github.com·19h·Hacker News

Why domain specific LLMs won’t exist: an intuition 🤖LLM

simianwords.bearblog.dev·5d·Hacker News

I’m building “Grammarly for LLMs” and I need blunt feedback on whether the optimization is actually useful 🪄Prompt Engineering

prompt-grader.app·6d·r/PromptEngineering, r/SideProject

Thoughts on Large Language Models (2023) 🤖LLM

nikola.plejic.com·3d·Hacker News

The pinnacle of enshittification, or Large Language Models 🤖LLM

blogs.gentoo.org·4d·Lobsters, Hacker News

Sampling from LLMs: Art and Science 🤖LLM

kachkach.com·3d·Hacker News

Syntax Is Easy, Semantics Is Hard: Evaluating LLMs for LTL Translation 🤖LLM

arxiv.org·1d

An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications 🤖LLM

arxiv.org·1d

Beyond LLM-as-a-Judge: Deterministic Metrics for Multilingual Generative Text Evaluation 🤖LLM

arxiv.org·2d

vLLM introduces memory optimizations for long-context inference 🤖LLM

github.com·5d·Hacker News

The Model Agreed, But Didn't Learn: Diagnosing Surface Compliance in Large Language Models 🤖LLM

arxiv.org·2d

Evaluation of Embedding-Based and Generative Methods for LLM-Driven Document Classification: Opportunities and Challenges 🤖LLM

arxiv.org·2d

Benchmarking LLM Tool-Use in the Wild 🪄Prompt Engineering

arxiv.org·1d·Hacker News

Distributed Interpretability and Control for Large Language Models ⚙️MLOps

arxiv.org·1d

When Do We Need LLMs? A Diagnostic for Language-Driven Bandits 🤖LLM

arxiv.org·2d

LLM Evaluation as Tensor Completion: Low Rank Structure and Semiparametric Efficiency 🤖LLM

arxiv.org·2d

Instruction-Tuned LLMs for Parsing and Mining Unstructured Logs on Leadership HPC Systems 🤖LLM

arxiv.org·2d

HYVE: Hybrid Views for LLM Context Engineering over Machine Data 🪄Prompt Engineering

arxiv.org·2d

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