Entropy-Guided Loop
How to make small models reason. A notebook that compares a reasoning model x a non reasoning model that runs a loop using logprobs found uncertainty. TLDR: A small, vendor-agnostic inference loop that turns token logprobs/perplexity/entropy into an extra pass and reasoning for LLMs.
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An educational Rust project for exporting and running inference on Qwen3 LLM family
PageIndex for Reasoning-Based RAG
vectifyai.notion.siteLarge Language Models (LLMs) are powerful tools for language understanding and generation, but they suffer from a fundamental limitation: the context window. Most LLMs can only process a limited number of tokens at a time. For instance, Claude does not allow uploading very long documents in full, which makes tasks like long document analysis or question answering particularly challenging.
Flow Matching model inference in C
github.comC-Flow Matching inference
GoalChain for goal-orientated LLM conversation flows
Empirical proof of SOTA LLM (GPT-5/Gemini-Pro/Claude-Pro) context saturation in complex engineering. Contains the "Misuraca Protocol" for deterministic logical segmentation to prevent entropy drift.