NLP

Natural Language Processing, Text Analysis, Language Models, Transformers

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Scoured 322 posts in 9.6 ms

Can LLMs save themselves from verbosity?

 🤖LLMs  Content type: Blog
dev.to··DEV

Phase transition in large language models and the criticality of natural languages

 🧠Deep Learning  Content type: Academic
arxiv.org·

heterodoxin/graphkv: Graph-guided KV cache compression for memory-efficient LLM inference.

 🤖LLMs  Content type: Code
github.com··r/LocalLLaMA

On-Device AI in SwiftUI Apps

 📈Optimization  Content type: Blog
dev.to··DEV

AutoMegaKernel: A Statically-Checked Agent Harness for Self-Retargeting Megakernel Synthesis

 🤖Transformers  Content type: Academic
arxiv.org··Hacker News

Unlocking the Power of RAG Systems with LangChain and Vector Databases

 🔍RAG  Content type: Blog
dev.to··DEV

The Amplifying Mirror: Locating and Steering the Partisan Direction inside a Large Language Model

 🤖LLMs  Content type: Academic
arxiv.org·

neo4-svg/cybersh: CYBER SH — Offline AI CLI for security researchers & devs. Runs local GGUF models via llama‑cpp‑python, no servers or API keys. Modes: Agent, Sec, Vibe, Code, Chat. Features file analysis, command execution, payload generation, recon planning, cyberpunk UI. Pure Python stdlib.

 🤖LLMs  Content type: Code
github.com··DEV

Geometry of Semantic Space: Comparative Study of Discrete and Continuous Models

 🔍Vector Databases  Content type: Academic
arxiv.org·

I turned a tiny WebGL arcade game into a browser-agent score challenge

 🤖LLMs  Content type: Blog
dev.to··DEV

The Neutral Mask: How RLHF Provides Shallow Alignment while Leaving Partisan Structure Intact in a Large Language Model

 🤖LLMs  Content type: Academic
arxiv.org·

zhongkaifu/TensorSharp: A C# inference engine for running large language models (LLMs) locally using GGUF model files. TensorSharp provides a console application, a web-based chatbot interface, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/Linux with full GPU capability

 🤖LLMs  Content type: Code
github.com··Hacker News

LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models

 🤖LLMs  Content type: Academic
arxiv.org·

I Built an Adversarial Eval Framework and Attacked 5 LLMs — Every Single One Failed

 🤖LLMs  Content type: Blog
dev.to··DEV

Zero and Few Shot Load Forecasting with Large Language Models

 🤖Machine Learning  Content type: Academic
arxiv.org·

harshuljain13/llm-inference-at-scale: A Practitioner handbook for production llm serving.

 🤖LLMs  Content type: Code
github.com··Hacker News

I Tested Claude Opus 4, GPT-4.1, GPT-4o, Sonnet 4, and Gemini 2.5 Pro on 10 Adversarial Scenarios. They All Broke on the Same One.

 🎭Anthropic Claude  Content type: Blog
dev.to··DEV

MeshTok: Efficient Multi-Scale Tokenization for Scalable PDE Transformers

 🤖LLMs  Content type: Academic
arxiv.org·

Hallucination Cascade: Analyzing Error Propagation in Multi-Agent LLM Systems

 🤖LLMs  Content type: Academic
arxiv.org·

I Benchmarked 3 Local LLMs on My Laptop — Here's What the Numbers Actually Show

 🤖LLMs  Content type: Blog
dev.to··DEV

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