ml-research

ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.

Don't trust an autoresearch paper at face value. Reviewer-side integrity forensics (self-consistency + fabrication), deterministic verdict. 61 signals: 46 integrity hack-patterns (families A–H, verdict-bearing) + 13 zero-weight AI writing-style impressions (AIS) + 2 advisory. Not an opaque AI-text classifier. The dual of ARIS.

Run a Parallel Autonomous ML Research Organization on your OpenClaw instance.

Research Agora: Claude Code skills, benchmarks & tools for ML researchers — paper writing, citation verification, experiment tracking, LaTeX automation

Skills that make your AI agent do ML research like a skeptical scientist, not a hype machine.

Research-first machine learning experiment tracker for comparing model metrics, scalar curves, artifacts, and experiment lineage.

Quantum-inspired Echo State Network for multi-agent behavior analysis (MABe challenge)

Code for the paper "2Mamba2Furious: Linear in complexity, competitive in accuracy"

Autonomous ML research agent skill (Agent Skills format). Designs experiments, deploys to Modal GPUs, tracks budget, iterates autonomously.

mBFT: Metacognitive Byzantine Fault Tolerance — reference implementation for Consensus-Driven Metacognition in Multi-Agent Systems

Model Evolution keeps the reasoning behind a machine-learning model connected to the exact data, code, runs, and artifacts that produced it.

Auto-updated AI Research Scientist and Research Engineer jobs, refreshed every 2 days. Top companies first. Free. By landed.

ML regression diagnosis: matched Banking77 localization studies, competing repairs and explicit ambiguity when evidence cannot identify a unique cause.

Automate code reviews for general code projects with modular parallel checks, config-driven scope, and clear reports.

Discord-native research operations toolkit for ML experimentation with Codex/Claude agents: relay orchestration, human-in-the-loop plan/task/worktree workflows, callback-driven long-running jobs, and hypothesis-driven research skills.

Claude Code skill for autonomous ML research — from topic to LaTeX paper

Automated Framework for Evaluating Chain-of-Thought Reasoning in LLMs.

Hypothesis-first experiment tracking for agent-driven ML research, wired into Claude Code.

GANs for learning from imbalance data

Benchmarking PEFT (LoRA vs adapters) for ECG segment classification using Wav2Vec2, HuBERT, and ECG-FM with full metric reporting and ablations.