# F(AI)2R: Who Did What, and Who Checked? Verifiable AI Provenance as an Executable Skill

arXiv: https://arxiv.org/abs/2607.25637 · HTML: https://mlsanity.com/paper/2607.25637/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 59 references that are in the map.
- First posted on arXiv 28 Jul 2026.

## Builds on (most cited first, 9 of 9)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Model Cards for Model Reporting](https://mlsanity.com/paper/1810.03993/) (2018)
- [PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows](https://mlsanity.com/paper/2508.02866/) (2025)
- [Packaging research artefacts with RO-Crate](https://mlsanity.com/paper/2108.06503/) (2021)
- [The strain on scientific publishing](https://mlsanity.com/paper/2309.15884/) (2023)
- [Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications](https://mlsanity.com/paper/1305.3506/) (2013)
- [PAV ontology: Provenance, Authoring and Versioning](https://mlsanity.com/paper/1304.7224/) (2013)
- [A quantitative and qualitative open citation analysis of retracted articles in the humanities](https://mlsanity.com/paper/2111.05223/) (2021)

## Built on by (most cited first, 1 of 1)

- [AIPOCH Open-Science: An Open-Source AI Research Workbench with Reproducible .science Packages](https://mlsanity.com/paper/2610.17110/) (2026)

## Abstract (arXiv)

F(AI)2R is FAIR research with AI in the loop, twice: an AI-assisted authoring pass and a machine-readable audit pass over every artefact. AI systems now draft, refactor, and verify research artefacts, yet their contributions are rarely recorded in a form a later human or machine can audit. Building on the original F(AI)2R experiment, we generalize its provenance model beyond scholarly writing into aiprov, a PROV-O extension covering any AI-in-the-loop artefact, and we package the method as an executable skill that an AI agent operates itself: setup asks the human operator for their ORCID ID, resolves their identity from the public registry, and scaffolds continuous integration that gates every push on graph conformance and publishes the current build of this very paper. The paper is its own case study. Every activity, claim, and source in its production is recorded in the repository's provenance graph under two invariants: no parentless claim, and verification rungs that only humans may grant.