AI Research / Multi-agent systems
Open-source multi-agent protocol for AI research agents. It pairs a tool-using Scientist with a question-only advisor that can only ask questions and approve plans, and the README includes quick-start setup plus notes on reproducing results on MLE-bench/Kaggle tasks.
The page clearly describes an AI-powered research-agent protocol, shows concrete repo contents, and gives usable setup and reproduction instructions. It also includes a specific mechanism that makes the project stand out: a question-only advisor that gates the next experiment with [APPROVED].
The crawl gives strong setup detail, but visitors still cannot tell the full runtime cost, exact model requirements, or how easy it is to apply beyond the paper-style benchmark workflow.
Last evaluated 22 days ago. Current rank #733. Down 2 spots in the rankings.
An autonomous research system that runs on a single workstation and aggressively checks its own claims with adversarial self-verification, replication, and calibration audits.
A sourced model and short report exploring whether Europe could train a sovereign frontier AI model using public compute it already owns, with reproducible code, datasets, and a PDF report.
An open-source research framework for structured LLM evaluation, claim verification, and source-grounded reflective reasoning. The repo describes modular components for retrieval, semantic scoring, skeptical claim checking, and benchmark-style epistemic assessment.
