AI Research / Evaluation / Verification Framework
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.
The page clearly presents an AI research project with a defined purpose: structured LLM evaluation and claim verification. The README gives enough substance for a public listing, including the framework’s modules, core capabilities, research motivation, and benchmark setup. It also shows concrete evidence of source retrieval, claim-level verification, and reproducible experimentation rather than a vague concept page.
The snapshot cuts off before the full benchmark and usage details, so a visitor cannot see setup instructions, runnable examples, or results quality in full. It also does not fully show how the included modules are wired together in practice or what inputs and outputs look like end to end.
Last evaluated 129 days ago. Current rank #1529. Down 64 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.
An MCP-based research agent that searches live web data through SQL and publishes reports with the full query and tool trajectory.
Uno is a research repository for speeding up LLM inference with discrete diffusion and lossless multi-token decoding. The repo includes inference, training, and evaluation code, plus installation steps, checkpoints, and example workflows.
An arXiv paper describing an open library of 163 procedural skills for research agents across 16 scientific areas, with versioned instruction files and accompanying reference material or runnable scripts.
