Free and Research Detectors

• arXiv
• arXiv
• Website
• Website
• Website
• Website

Leading Commercial Detectors

• Website
• Website

• [OpenAI
• [HuggingFace
• [GitHub

Anthropic (Claude)

• API Docs

Google (Gemini)

• Google AI Studio

Meta (Llama)

• Llama

OpenAI

• Platform Docs

Other Notable Providers

• Website
• Website
• Website
• Website

Domain-Specific Adaptations

• mattprusak/autoresearch-genealogy - history research.
• ArchishmanSengupta/autovoiceevals - or-revert prompt edits to harden voice AI agents across Vapi, Smallest AI, and ElevenLabs.
• chrisworsey55/atlas-gic - or-revert loop to trading agents, optimizing prompts and portfolio orchestration against rolling Sharpe ratio instead of model loss.
• RightNow-AI/autokernel
• Rkcr7/autoresearch-sudoku - built solvers on hard benchmark sets.
• jeongph/autospec - language business rules and autonomously builds a Spring Boot service with tests via the keep-or-revert loop. Evaluates with Gradle build + JUnit XML. 119-line skeleton to 950 lines in 5 cycles.
• Agent-Analytics/autoresearch-growth - page positioning and A/B test candidates, using analytics snapshots and measured experiment results to seed subsequent rounds.
• ElliotXie/autozyme - agent framework that applies the autoresearch keep-or-revert loop to CPU-side scientific software: profile a target function, generate one optimization candidate, benchmark for speed while preserving the original outputs, keep or revert, repeat.
• vlasenkoalexey/tpu_performance_autoresearch_wiki - or-revert loop to TPU model performance (MFU / tokens-per-sec) on v6e hardware: profiles each run through an XProf MCP server, makes one model-code change per experiment, and keeps or reverts against measured MFU. Pairs the loop with a Karpathy-style LLM wiki for domain knowledge and per-experiment optimization traces; includes Llama3-8B and Qwen3-8B case studies across JAX and torchax lanes.

Evaluation & Benchmarks

• snap-stanford/MLAgentBench - 10 to BabyLM.
• chchenhui/mlrbench - Bench: Evaluating AI agents on open-ended ML research. 201 tasks from NeurIPS/ICLR/ICML workshops.
• gersteinlab/ML-Bench - level code.
• THUDM/AgentBench - as-Agent evaluation across 8 distinct environments. ICLR 2024.

General-Purpose Descendants

• kayba-ai/recursive-improve - improvement framework where agents capture execution traces, analyze failure patterns, and apply targeted fixes with keep-or-revert evaluation.
• vukrosic/auto-research - only control plane for an open autonomous AI research lab — file-based operating model for human direction and agent execution.
• uditgoenka/autoresearch
• leo-lilinxiao/codex-autoresearch - native autoresearch skill with resume support, lessons across runs, optional parallel experiments, and mode-specific workflows.
• supratikpm/gemini-autoresearch - native: uses Google Search grounding as a live verification source inside the loop, true headless overnight mode via --yolo --prompt, and 1M token context. Also works in Antigravity IDE via .agents/skills/.
• davebcn87/pi-autoresearch
• drivelineresearch/autoresearch-claude-code - autoresearch`, with a clean experiment-loop workflow and a concrete biomechanics case study.
• greyhaven-ai/autocontext - loop control plane for repeated agent improvement, with evaluation, persistent knowledge, staged validation, and optional distillation into cheaper local runtimes.
• jmilinovich/goal-md
• james-s-tayler/lazy-developer - instance execution.
• mutable-state-inc/autoresearch-at-home - config syncing, hypothesis exchange, and swarm-style coordination across many single-GPU agents.
• zkarimi22/autoresearch-anything
• Entrpi/autoresearch-everywhere - platform expansion that auto-detects hardware config and starts the loop. The "glue and generalization" half of autoresearch.
• ShengranHu/ADAS - agents that invent novel agent architectures by programming them in code.
• MaximeRobeyns/self_improving_coding_agent - Improving Coding Agent that edits its own codebase. ICLR 2025 Workshop paper demonstrating scaffold-level self-improvement on coding benchmarks.
• peterskoett/self-improving-agent - improving agent architecture with reflection and meta-learning cycles.
• metauto-ai/HGM - Gödel Machine** for coding agents — applies self-improvement to SWE-bench performance via meta-level optimization.
• gepa-ai/gepa - Pareto)** — ICLR 2026 Oral. Reflective prompt evolution that outperforms RL (GRPO) on benchmarks. Optimizes any textual parameters against any metric using natural language reflection.
• MrTsepa/autoevolve - inspired autoresearch for self-play: mutate code strategies, evaluate head-to-head, rate with Elo/Bradley-Terry, branch from the Pareto front. Agent reads match traces to target mutations. Works as a Claude Code skill.
• HKUDS/ClawTeam
• Orchestra-Research/AI-Research-SKILLs - loop architecture (inner optimization + outer synthesis).
• WecoAI/aideml - search ML engineering agent that autonomously improves model performance via iterative code generation and evaluation.
• weco.ai
• sentient-agi/EvoSkill
• SeeleAI/Thoth - first Claude Code and Codex runtime for autoresearch, with durable runs, locked work items, visible ledgers, and reviewable verdicts.
• Necmttn/ax
• junjunjunbong/research-loop - style Agent Skill for Codex and Claude Code with a deterministic runner, plan-hash approval, isolated Git worktrees, authoritative metric evaluation, and an append-only experiment ledger.
• xieyulai/steer

GitHub Organizations

• awesome-autoresearch - 04-09

Platform Ports & Hardware Forks

• gianfrancopiana/openclaw-autoresearch - autoresearch; autonomous experiment loop for any optimization target with statistical confidence scoring.
• miolini/autoresearch-macos
• trevin-creator/autoresearch-mlx - native Apple Silicon port that keeps the upstream fixed-budget `val_bpb` loop while removing the PyTorch/CUDA dependency entirely.
• jsegov/autoresearch-win-rtx - native RTX fork focused on consumer NVIDIA GPUs, with explicit VRAM floors and a practical desktop setup path.
• iii-hq/n-autoresearch - GPU autoresearch infrastructure with structured experiment tracking, adaptive search strategy, crash recovery, and queryable orchestration around the classic `train.py` loop.
• lucasgelfond/autoresearch-webgpu - browser, and feed results back into the loop without a Python setup.
• tonitangpotato/autoresearch-engram - weighted retrieval of cross-session knowledge for improved experiment continuity.
• upstream issue #208
• ArmanJR-Lab/autoautoresearch - experiment comparison (baseline vs director-guided) with detailed stall analysis.

Related Resources

• ai-agents-2030/awesome-deep-research-agent
• YoungDubbyDu/LLM-Agent-Optimization
• VoltAgent/awesome-ai-agent-papers
• masamasa59/ai-agent-papers
• tmgthb/Autonomous-Agents
• HKUST-KnowComp/Awesome-LLM-Scientific-Discovery
• openags/Awesome-AI-Scientist-Papers
• agenticscience.github.io
• dspy.ai/GEPA
• OpenAI Cookbook: Self-Evolving Agents - style reflective evolution.
• WecoAI/awesome-autoresearch

Research-Agent Systems

• aiming-lab/AutoResearchClaw - to-end research pipeline that turns a topic into literature review, experiments, analysis, peer review, and paper drafts; broader than autoresearch, but clearly in the same lineage.
• OpenRaiser/NanoResearch - to-end autonomous research engine that plans experiments, generates code, runs jobs locally or on SLURM, analyzes real results, and writes papers grounded in those outputs.
• wanshuiyin/Auto-claude-code-research-in-sleep - first research workflows for Claude Code and other agents, centered on autonomous literature review, experiments, paper iteration, and cross-model critique.
• Sibyl-Research-Team/AutoResearch-SibylSystem - agent research iteration, GPU experiment execution, and a self-evolving outer loop.
• eimenhmdt/autoresearcher - source package for automating scientific workflows, currently centered on literature-review generation with an ambition toward broader autonomous research.
• hyperspaceai/agi - to-peer research network where autonomous agents run experiments, gossip findings, maintain CRDT leaderboards, and archive results to GitHub across multiple research domains.
• SakanaAI/AI-Scientist
• SakanaAI/AI-Scientist-v2 - level automated scientific discovery via agentic tree search. Removes template dependency from v1, generalizes across research domains.
• HKUDS/AI-Researcher - to-end research automation: hypothesis → experiments → manuscript → peer review. Production version at [novix.science](https://novix.science/chat).
• openags/Auto-Research
• SamuelSchmidgall/AgentLaboratory - to-end autonomous research workflow: idea → literature review → experiments → report. Supports both autonomous and co-pilot modes.
• AgentRxiv
• JinheonBaek/ResearchAgent - agent review and feedback loops.
• du-nlp-lab/MLR-Copilot
• MASWorks/ML-Agent
• PouriaRouzrokh/LatteReview - code Python package for **automated systematic literature reviews** via AI-powered agents.
• LitLLM/LitLLM - powered literature review assistant using RAG for accurate, well-structured related-work sections in academic writing.
• Agent Laboratory - phase research pipeline: Literature Review → Experimentation → Report Writing, with specialized agents for each phase.
• Human-Agent-Society/CORAL - agent evolution for open-ended discovery ([arXiv:2604.01658](https://arxiv.org/abs/2604.01658)). Long-running agents with shared persistent memory, asynchronous execution, and heartbeat-based interventions; SOTA on 10 math/algorithmic/systems tasks.
• skyllwt/OmegaWiki - centric full-lifecycle research platform built on Claude Code, realizing Karpathy's LLM-Wiki vision. 20+ skills cover the full loop: ingest → ideate → novelty check → experiment design / run / eval → paper writing. Research state lives in a structured knowledge wiki with an interactive graph.
• AweAI-Team/AiScientist - horizon ML research lab with hierarchical orchestration and File-as-Bus coordination — workspace files act as the durable system of record. Drives autonomous paper-reproduction (PaperBench) and competition-style MLE-Bench iteration loops under fixed compute/time budgets. ([arXiv 2604.13018](https://arxiv.org/abs/2604.13018))
• kaust-ark/ARK
• skyllwt/AutoSci - centric full-lifecycle research platform built on Claude Code, realizing Karpathy's LLM-Wiki vision. 20+ skills cover the full loop: ingest → ideate → novelty check → experiment design / run / eval → paper writing. Research state lives in a structured knowledge wiki with an interactive graph.
• happyhappy-jun/writing-driven-autoresearch - style harness that keeps a submittable paper from the first minute and drives every experiment from the claims in that draft, looping modify → measure → verify → revise. 1st place at the [Ralphthon@ICML 2026](https://luma.com/hjuo7auc) autonomous-research hackathon.
• AutoResearch-Factory/Agon - to-end research orchestrator built on one cornerstone principle, Prompt Economy (reusable loops, not one-off prompts), plus five supporting rules; runs scientist/coder/auditor loops across 10+ disciplines, same reusable-loop lineage as autoresearch but scaled to full research programs.

Discord Servers

• Learn Prompting
• Hugging Face Discord
• FlowGPT - E, Stable Diffusion, Claude.

Forums and Platforms

• OpenAI Developer Community
• Hugging Face Community - source AI collaboration.
• DeepLearning.AI Community
• LessWrong - depth technical posts on AI capabilities and safety.
• AI Alignment Forum
• CivitAI

GitHub Organizations

• LangChain - source LLM app framework. 100K+ stars.
• Promptslab - Engineering | LLMs
• Hugging Face
• OpenAI - source models, benchmarks, and tools.

Reddit

• r/PromptEngineering
• r/ChatGPT
• r/LocalLLaMA - source LLMs locally.
• r/ClaudeAI
• r/MachineLearning - oriented ML research discussions.
• r/OpenAI
• r/StableDiffusion
• r/ChatGPTPromptGenius

• OpenAI Discord
• PromptsLab Discord
• Learn Prompting
• r/ChatGPT Discord
• MidJourney Discord

Free Platform Courses

• Hugging Face LLM Course - driven course covering transformers, fine-tuning, building reasoning models.
• Hugging Face AI Agents Course

Free Short Courses

• Building Systems with the ChatGPT API - step LLM system design for production. (DeepLearning.AI)
• AI Agents in LangGraph
• Building Agentic RAG with LlamaIndex
• Functions, Tools and Agents with LangChain

University and Platform Courses

• Prompt Engineering Specialization (Vanderbilt) - course series by Dr. Jules White covering foundational to advanced PE. (Coursera)
• Generative AI with LLMs (DeepLearning.AI + AWS)
• Stanford CS336: Language Modeling from Scratch - to-end. (Stanford, 2024–2026)
• MIT 6.S191: Introduction to Deep Learning
• The Complete Prompt Engineering for AI Bootcamp - 5, DSPy, LangGraph, agent architectures. 58K+ ratings. (Udemy, updated Feb 2026)

• ChatGPT Prompt Engineering for Developers
• Prompt Engineering for Vision Models
• ChatGPT for Everyone
• Introduction to Prompt Engineering
• Advanced Prompt Engineering
• Introduction to Generative AI Agents for Business Professionals
• Introduction to Prompt Hacking
• Introduction to Generative AI in Marketing
• Advanced Prompt Hacking
• Image Creation with DALL·E 3
• AI Safety
• Runway ML for Everyone
• Advanced OpenAI Playground
• Boost Your Day-to-Day Efficiency With Generative AI
• Introduction to Large Language Models (LLMs) for Business Professionals
• Introduction to Retrieval-Augmented Generation (RAG) for Business Professionals
• Introduction to Generative AI for Business Professionals

Leaderboards and Meta-Benchmarks

• Leaderboard
• Website
• Leaderboard

Major Benchmarks (2024–2026)

• Website
• GitHub
• arXiv
• Website
• Leaderboard
• Website
• Leaderboard
• Paper
• arXiv
• GitHub
• GitHub

Prompt and Instruction Datasets

• HuggingFace
• HuggingFace
• HuggingFace

Red Teaming and Adversarial Datasets

• Website
• arXiv