🧠 LLM - yfff · Scour

dReLU Sparsification: Recovering LLM Performance with 150B Token Pretraining

hackernoon.com·12h

Understanding Large Language Models (LLMs)

insightsonindia.com·2d

Min-p sampling for LLMs

thoughtworks.com·14h

brendanhogan/base-model-agents

github.com·3h

Optimizing LLM Inference: Sparse Activation, MoE, and Gated-MLP Efficiency

hackernoon.com·1d

Sakana AI Introduces Doc-to-LoRA and Text-to-LoRA: Hypernetworks that Instantly Internalize Long Contexts and Adapt LLMs via Zero-Shot Natural Language

marktechpost.com·18h

Evaluating LLMs using semantic entropy

research.thoughtworks.com·14h

Tokenization, Fusion and Decoupling: Bridging the Granularity Mismatch Between Large Language Models and Knowledge Graphs

arxiv.org·1d

The 4 LLM Evaluation Frameworks: How to Benchmark AI Like Google and OpenAI Do

pub.towardsai.net

·22h

Current language model training leaves large parts of the internet on the table

the-decoder.com

·47m

Large language model evaluation: The key to GenAI success BasicAdvancedThumbnailSocial MediaCloud ServicesPersonalizationPermissionsBlueprintMeta tagsTags

thoughtworks.com·14h

LLM now provides tools for working with embeddings

simonwillison.net·2d

Some notes on unreliability of LLM APIs

andrewpwheeler.com·19h·

Discuss: Hacker News

Asura: Looped Language Models done better

neel04.github.io·2d·

Discuss: Hacker News

Part 1: Tokenization, Building an LLM From Scratch in Rust

tag1.com·2d

ConstraintBench: Benchmarking LLM Constraint Reasoning on Direct Optimization

arxiv.org·1d

LLM-Based Evolution as a Universal Optimizer

imbue.com·15h·

Discuss: Hacker News

Unsloth Dynamic 2.0 GGUFs

unsloth.ai·3h·

Discuss: Hacker News

Understanding Large Language Models: The Engines Behind Today's AI Revolution

dev.to·2d·

Discuss: DEV

A family of large language models for materials research with insights into model adaptability in continued pretraining

nature.com·1d

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