ECAI Artifact Evaluation
Start with a correction that saves authors from importing the wrong workflow: ECAI does not run an
ACM/IEEE-style artifact-evaluation track with a separate badge committee. There is no
"Artifacts Available / Functional / Reusable / Reproduced" pipeline as at ACM SIGSOFT venues, and
no separate artifact deadline to hit after acceptance. In ECAI, the reproducibility story is
carried by the paper and its supplement and judged by the same reviewers who read the paper,
during the one review round.
That makes the "artifact" a submission-time asset, not a post-acceptance badge chase. Its job is
to make the reviewer trust the claim inside a 7-page body. (Confirm on the current call whether the
edition adds any optional reproducibility checklist or appendix mechanism — this is 待核实 per
cycle and can differ between a standalone ECAI and the joint IJCAI-ECAI 2026.)
Match the artifact to the contribution shape
ECAI is a general-AI venue, so "artifact" means different things:
| Contribution shape |
The credibility artifact is... |
| Theory / KR / argumentation |
A complete proof appendix (full proofs the body only sketches) plus, if applicable, a reference solver/encoding |
| Planning / search / optimization |
The domain files, instances, seeds, and a runnable implementation reproducing the reported node/quality numbers |
| Machine learning |
Code, data (or a loader), configs, seeds, and cached outputs so results reproduce without live API calls |
| Multi-agent systems |
The environment, agent code, and the exact evaluation protocol (episodes, seeds, metrics) |
| Applied AI (PAIS) |
Enough of the pipeline and (sanitized) data to make the deployment claim credible |
What "good" looks like at review time
- Anonymized. The supplement is read under double-blind review; strip repository owners,
institution names, and system names that identify you (
ecai-submission).
- Self-contained. A reviewer opens it once, in a short window; it must run or be readable
without chasing dependencies or your lab's private data.
- Decision-critical content stays in the body. The supplement holds support (full proofs,
extra tables, code) — not the claim itself. Nothing a reviewer needs to judge the paper may
live only in the supplement (
ecai-supplementary).
- Proportional. Match effort to the claim: a theory paper's artifact is a rigorous proof
appendix, not a Docker image; an empirical paper's artifact is a runnable, seeded package.
A pragmatic checklist (adapt, don't badge-chase)
[ ] Full proofs present for every theorem the body sketches (theory work)
[ ] Code runs from a clean checkout with a documented entrypoint (empirical work)
[ ] Data included or a script fetches a versioned public source; seeds fixed
[ ] Cached model/API outputs included so results do not re-sample at run time
[ ] A short README maps each paper claim/table -> the file that reproduces it
[ ] Archive anonymized: no owner, institution, funding, or system-name leaks
[ ] Total size and runtime reasonable for a reviewer's one-pass read
Do not import the wrong machinery
- No ACM/IEEE badges. Do not promise "Artifacts Evaluated - Reusable" or design around a badge
committee — none exists at ECAI. Credibility is reviewer-judged, in-band.
- No separate artifact-track deadline. Everything ships with the paper (abstract 12 Jan / paper
19 Jan for IJCAI-ECAI 2026); there is no later artifact submission.
- Not a leaderboard. ECAI values understanding (a proof, a fair comparison) over a single
benchmark number; an artifact that only re-prints a leaderboard score misses the venue's bar
(
ecai-experiments).
Post-acceptance: make it permanent and open
Once accepted, convert the anonymized supplement into a permanent, open release to match ECAI's
open-access ethos:
- Deposit code/data in a DOI-issuing archive (e.g. Zenodo/Software Heritage) with an open license.
- De-anonymize repository owners and restore acknowledgements (
ecai-camera-ready).
- Put the permanent link in the camera-ready so the open-access paper points to a stable artifact.
Output format
[Artifact type] proof appendix / runnable code+data / environment+protocol / deployment pipeline
[Anonymity] clean / leaks: <where>
[Claim map] each theorem/table -> proof or reproducing file
[Self-containment] runs/readable in one pass? missing deps: <list>
[Reality check] no ACM/IEEE badge assumed; nothing decision-critical hidden in the supplement
[Post-acceptance] DOI archive + open license + de-anonymized link planned for camera-ready
Source: brycewang-stanford/Awesome-Journal-Skills → ECAI-Skills/skills/ecai-artifact-evaluation/SKILL.md
1---2name: ecai-artifact-evaluation3description: Use when planning the reproducibility/artifact story for an ECAI paper — noting that ECAI/FAIA has NO ACM/IEEE-style artifact-badging committee, so credibility is carried by the paper and its supplement and judged by the same reviewers, and adapting an ML-style reproducibility package (or a complete proof appendix for theory work) to that reality.4---567# ECAI Artifact Evaluation89Start with a correction that saves authors from importing the wrong workflow: **ECAI does not run an10ACM/IEEE-style artifact-evaluation track with a separate badge committee.** There is no11"Artifacts Available / Functional / Reusable / Reproduced" pipeline as at ACM SIGSOFT venues, and12no separate artifact deadline to hit after acceptance. In ECAI, the reproducibility story is13**carried by the paper and its supplement and judged by the same reviewers** who read the paper,14during the one review round.1516That makes the "artifact" a **submission-time asset**, not a post-acceptance badge chase. Its job is17to make the reviewer trust the claim inside a 7-page body. (Confirm on the current call whether the18edition adds any optional reproducibility checklist or appendix mechanism — this is **待核实** per19cycle and can differ between a standalone ECAI and the joint IJCAI-ECAI 2026.)2021## Match the artifact to the contribution shape2223ECAI is a **general-AI** venue, so "artifact" means different things:2425| Contribution shape | The credibility artifact is... |26|---|---|27| Theory / KR / argumentation | A **complete proof appendix** (full proofs the body only sketches) plus, if applicable, a reference solver/encoding |28| Planning / search / optimization | The **domain files, instances, seeds**, and a runnable implementation reproducing the reported node/quality numbers |29| Machine learning | Code, data (or a loader), configs, seeds, and **cached outputs** so results reproduce without live API calls |30| Multi-agent systems | The environment, agent code, and the exact evaluation protocol (episodes, seeds, metrics) |31| Applied AI (PAIS) | Enough of the pipeline and (sanitized) data to make the **deployment claim** credible |3233## What "good" looks like at review time3435- **Anonymized.** The supplement is read under double-blind review; strip repository owners,36 institution names, and system names that identify you (`ecai-submission`).37- **Self-contained.** A reviewer opens it once, in a short window; it must run or be readable38 without chasing dependencies or your lab's private data.39- **Decision-critical content stays in the body.** The supplement holds *support* (full proofs,40 extra tables, code) — not the claim itself. Nothing a reviewer needs to *judge* the paper may41 live only in the supplement (`ecai-supplementary`).42- **Proportional.** Match effort to the claim: a theory paper's artifact is a rigorous proof43 appendix, not a Docker image; an empirical paper's artifact is a runnable, seeded package.4445## A pragmatic checklist (adapt, don't badge-chase)4647```text48[ ] Full proofs present for every theorem the body sketches (theory work)49[ ] Code runs from a clean checkout with a documented entrypoint (empirical work)50[ ] Data included or a script fetches a versioned public source; seeds fixed51[ ] Cached model/API outputs included so results do not re-sample at run time52[ ] A short README maps each paper claim/table -> the file that reproduces it53[ ] Archive anonymized: no owner, institution, funding, or system-name leaks54[ ] Total size and runtime reasonable for a reviewer's one-pass read55```5657## Do not import the wrong machinery5859- **No ACM/IEEE badges.** Do not promise "Artifacts Evaluated - Reusable" or design around a badge60 committee — none exists at ECAI. Credibility is reviewer-judged, in-band.61- **No separate artifact-track deadline.** Everything ships with the paper (abstract 12 Jan / paper62 19 Jan for IJCAI-ECAI 2026); there is no later artifact submission.63- **Not a leaderboard.** ECAI values understanding (a proof, a fair comparison) over a single64 benchmark number; an artifact that only re-prints a leaderboard score misses the venue's bar65 (`ecai-experiments`).6667## Post-acceptance: make it permanent and open6869Once accepted, convert the anonymized supplement into a **permanent, open** release to match ECAI's70open-access ethos:7172- Deposit code/data in a DOI-issuing archive (e.g. Zenodo/Software Heritage) with an open license.73- De-anonymize repository owners and restore acknowledgements (`ecai-camera-ready`).74- Put the permanent link in the camera-ready so the open-access paper points to a stable artifact.7576## Output format7778```text79[Artifact type] proof appendix / runnable code+data / environment+protocol / deployment pipeline80[Anonymity] clean / leaks: <where>81[Claim map] each theorem/table -> proof or reproducing file82[Self-containment] runs/readable in one pass? missing deps: <list>83[Reality check] no ACM/IEEE badge assumed; nothing decision-critical hidden in the supplement84[Post-acceptance] DOI archive + open license + de-anonymized link planned for camera-ready85```8687---8889**Source:** [`brycewang-stanford/Awesome-Journal-Skills`](https://github.com/brycewang-stanford/Awesome-Journal-Skills) → `ECAI-Skills/skills/ecai-artifact-evaluation/SKILL.md`