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 118 days ago. Current rank #1385. Down 55 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.
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.
A research post from Telem AI measuring cold-start latency across nine web-search APIs, with cache behavior, tail latency, and agent-query comparisons.
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.
