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CONTRIBUTING.md

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+# Contributing
+
+Contributions are welcome through pull requests or issues.
+
+## Entry format
+
+Please provide:
+
+```text
+Year | Paper | Domain | Target/observable | Access | Auxiliary data/prior |
+Attack or defense | Venue/status | Paper URL | Code URL (optional)
+```
+
+Use an official publisher, conference, proceedings, OpenReview, ACL Anthology, PMLR, CVF/ECVA, USENIX, DOI, or arXiv link whenever possible.
+
+## Status labels
+
+- `peer-reviewed`: published in proceedings or a journal.
+- `accepted`: officially accepted but proceedings are not yet available.
+- `preprint`: arXiv or another non-peer-reviewed manuscript.
+- `withdrawn submission`: a submission record that was withdrawn; do not label it as a conference publication.
+
+## Scope
+
+Classical model inversion uses information exposed by a trained model to reconstruct private training information or sensitive characteristics. Please label the following as **adjacent reconstruction** unless the paper explicitly studies the classical MIA threat model:
+
+- gradient inversion from shared training gradients;
+- training-data extraction by prompting a generative model;
+- model or embedding inversion for interpretation rather than privacy attacks;
+- inversion of unlearning or concept-erasure mechanisms;
+- attacks on synthetic-data releases.
+
+## Quality checks
+
+Before submitting:
+
+1. Search the repository for duplicate titles and earlier versions.
+2. Merge preprint and final versions into one entry when they represent the same work.
+3. Verify authors, title, venue, year, pages, DOI, and current publication status.
+4. State the exposed interface and recovered target rather than using only “white-box” or “black-box”.
+5. Avoid copying abstracts; add at most one original sentence describing the contribution.