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What you can do with Veri Repro

VeriRepro is a Python package that checks whether a computational paper's claims are backed by its repository, environment, and execution evidence, and writes a PASS, FAIL, or PARTIAL reproduction report.

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XiantingWu/VeriRepro on GitHub

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What do you want to do?

4 use cases

  • Plan a paper's reproduction without running its code

    Map a paper's claims to repository and environment evidence with no third-party code execution.

    View prompt
    Using the VeriRepro repo (XiantingWu/VeriRepro), install the verirepro package and run `verirepro reproduce <paper-id> --no-execute --no-llm` for the paper <paper-id>. Confirm the workspace contains repository-plan.json and environment-plan.json and that no experiment code was executed, then summarize the report.json status and the planned steps.

  • Verify a paper's metrics by running its code in a sandbox

    Run a paper's repository in the Docker boundary and get a PASS, FAIL, or PARTIAL verdict.

    View prompt
    Using the VeriRepro repo (XiantingWu/VeriRepro), run `verirepro doctor --strict` and then `verirepro reproduce <paper-id>` for the paper <paper-id>. Expected output is a workspace with report.json and a PASS, FAIL, or PARTIAL status. Verify that any PASS is backed by evidence-authorized scalar comparisons and not just a zero exit code.

  • Check paper discovery against the 15-paper smoke corpus

    Run the deterministic discovery and evidence gate on pinned public papers.

    View prompt
    Using the VeriRepro repo (XiantingWu/VeriRepro), clone the repository, install it with `python -m pip install -e '.[dev]'`, and run `python scripts/run_real_paper_smoke.py --require-top1 --require-evidence`. Expected output is a gate result over the 15 pinned papers. Verify the gate result and report any failing papers without claiming that all 15 were fully reproduced.

  • Score agent reproduction runs with the ReproBench adapter

    Turn each agent's reproduction task into a result file and a summary with the ReproBench commands.

    View prompt
    Using the VeriRepro repo (XiantingWu/VeriRepro), run `verirepro-reprobench task.json --output result.json` for the task file <task-file>, then run `verirepro-reprobench-summary results/*.json --output summary.json`. Expected output is a per-task result and a combined summary. Verify that the task file had no local, file, or insecure HTTP paper sources and that operator interventions are recorded.

How to use Veri Repro

  1. Check you have what it needs: Python with pip to install the verirepro package from PyPI; A pinned arXiv ID, DOI, PDF URL, or local PDF of the paper; Docker, only if you want third-party experiment code to execute.
  2. Open XiantingWu/VeriRepro on GitHub and read the README and license.
  3. Install the published package with python -m pip install verirepro.
  4. Check the local setup with verirepro doctor --json.
  5. Plan the reproduction of a pinned smoke-corpus paper with verirepro plan 2103.00020v1.
  6. Run the planning-only reproduction with verirepro reproduce 2103.00020v1 --no-execute --no-llm and open the generated report.json or report.md.

These steps come from our top use case, Plan a paper's reproduction without running its code, which also has a copy-paste agent prompt.

Veri Repro alternatives · Best AI repos for Research

About this repo

Requirements

  • Python with pip to install the verirepro package from PyPI
  • A pinned arXiv ID, DOI, PDF URL, or local PDF of the paper
  • Docker, only if you want third-party experiment code to execute
  • An OpenAI-compatible model endpoint, only if you want model-assisted analysis
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Questions about Veri Repro

What is Veri Repro?

VeriRepro is a Python package that checks whether a computational paper's claims are backed by its repository, environment, and execution evidence, and writes a PASS, FAIL, or PARTIAL reproduction report. It is an open-source project on GitHub: https://github.com/XiantingWu/VeriRepro.

Who is Veri Repro for?

Researchers and reviewers who need to check whether a paper's reported results were actually reproduced, not just whether its code ran.

What can I do with Veri Repro?

4 use cases so far, for example: Plan a paper's reproduction without running its code; Verify a paper's metrics by running its code in a sandbox; Check paper discovery against the 15-paper smoke corpus. Each has steps and a copy-paste agent prompt.

What do I need to run Veri Repro?

Python with pip to install the verirepro package from PyPI; A pinned arXiv ID, DOI, PDF URL, or local PDF of the paper; Docker, only if you want third-party experiment code to execute; An OpenAI-compatible model endpoint, only if you want model-assisted analysis.

What are alternatives to Veri Repro?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Veri Repro safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.