💬 LLMs - krks.gbr · Scour

LLM (Large Language Model) 🤖AI

ministryoftesting.com·2d

Learning is Forgetting: LLM Training As Lossy Compression 🤖AI

arxiv.org·3h

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

github.com·16h·Hacker News

Using LLMs as Classifiers 🤖AI

medium.com·4d

LaCy: What Small Language Models Can and Should Learn is Not Just a Question of Loss 🤖AI

machinelearning.apple.com·1d

Thoughts on Large Language Models (2023) 🤖AI

nikola.plejic.com·3d·Hacker News

Recursive Language Models - A Systematic Approach to Large-Scale Document Analysis – Part I. 🤖AI

constitutionaldiscourse.com·2d

What Rebuilding GPT-2 From Scratch Taught Me About How LLMs Really Work 📝PKM

medium.com·3d

Type-Guided Constrained Decoding: How to Stop LLMs from Hallucinating Code 🔷Type Systems

medium.com·6d

LLM inference engine from scratch in C++ 🔷Type Systems

anirudhsathiya.com·4d·Hacker News

🧠 Bidirectional Encoder Representations from Transformers (BERT) 🧠Cognitive AI

medium.com·5d

Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning 🤖AI

arxiv.org·3h

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

arxiv.org·1d

vLLM introduces memory optimizations for long-context inference 🤖AI

github.com·5d·Hacker News

AsyncTLS: Efficient Generative LLM Inference with Asynchronous Two-level Sparse Attention 🤖AI

arxiv.org·3h

SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs λFunctional Programming

arxiv.org·3h

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

arxiv.org·1d

Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization 🤖AI

arxiv.org·3h

A Decomposition Perspective to Long-context Reasoning for LLMs 🔷Type Systems

arxiv.org·3h

Just Pass Twice: Efficient Token Classification with LLMs for Zero-Shot NER 🤖AI

arxiv.org·2d

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