Claude Code learns from your corrections: self-correcting memory that compounds over 50+ sessions. Context engineering, parallel worktrees, agent teams, and 17 battle-tested skills.

Enhancing LLMs with LoRA

🔥 [CVPR2024] Official implementation of "Self-correcting LLM-controlled Diffusion Models (SLD)

Explore concepts like Self-Correct, Self-Refine, Self-Improve, Self-Contradict, Self-Play, and Self-Knowledge, alongside o1-like reasoning elevation🍓 and hallucination alleviation🍄.

Cognitive prisms for structural analysis — any domain, any model. 1000+ experiments, 58 prisms, 27 scan modes. The cheapest model + right prism beats the most expensive without one. Cross-architecture validated: Claude + Gemini converge on the same structural laws.

[ICLR 2025] SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction

List of papers on Self-Correction of LLMs.

A comrephensive collection of learning from rewards in the post-training and test-time scaling of LLMs, with a focus on both reward models and learning strategies across training, inference, and post-inference stages.

Scalable long read self-correction and assembly polishing with multiple sequence alignment

[ACL'24] Code and data of paper "When is Tree Search Useful for LLM Planning? It Depends on the Discriminator"

Introduces a comprehensive agent-based framework for guided software development (GSD)

[ICLR 2025] Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate

SCoRe: Training Language Models to Self-Correct via Reinforcement Learning

[ICLR 2025 SSI-FM] Self-Taught Self-Correction for Small Language Models

Official Implementation of "ProgCo: Program Helps Self-Correction of Large Language Models" (Accpeted at ACL2025 Main)

Self-correction engine for AI coding agents - implements the Reflexion paper (Shinn et al., 2023) as a Rust MCP server. Turns failures into persistent, searchable lessons that prevent the same mistakes across sessions.

Spec-driven coding skills for AI agents: plan with acceptance criteria, self-correct from feedback, and remember reusable project knowledge.

🕸️ Self-Optimizing Multi-Agent AI System on AWS — Routes tasks to specialized AI agents (Coder, Researcher, Summarizer) with auto-verification, self-correction, and vector-cached memory. Built with Step Functions, Bedrock, and OpenSearch Serverless.

A recursive alignment framework for cognitive coherence, belief tracking, and contradiction repair.

Role-aware Claude Code plugin: 10 specialist agents (frontend, backend, QA, a11y, perf, security, architect, debugger, code-reviewer, docs), 15 domain commands, 8 skills, and a SQLite-backed learning crystal that compounds your corrections across sessions.