Fixing LLM memory degradation in long coding sessions
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. Long-session LLM memory degradation (entropy) is the silent killer of complex coding projects.
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Long term Memory and 50M token window for LLM
huggingface.coJoin the discussion on this paper page
Local persistent memory store for LLM applications including claude desktop, github copilot, codex, antigravity, etc.
GPTLint
github.coman OSS standard for LLM-based code review
Git for LLMs
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We built a multi-stage retrieval system that scores among the best on LongMemEval, using only open-source models. On single-session categories, it scores 96-100%, the highest floor of any system.