Skills Development Packaging Artifacts for Academic Reproducibility

Packaging Artifacts for Academic Reproducibility

v20260724
ijcai-artifact-evaluation
This guide outlines best practices for packaging research artifacts (code, data, proofs, models) submitted for major AI conferences like IJCAI. It helps researchers create convincing, anonymous, and reproducible evidence to support their claims, even when formal artifact evaluation tracks are unavailable.
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Overview

IJCAI Artifact Evaluation

Use this for artifact packaging around IJCAI. Treat the current reproducibility guidelines and supplementary-material rules as controlling; do not assume a separate formal artifact evaluation track unless the current cycle announces one.

Package design

  • Decide what reviewers need to classify the results as convincing or credible: proofs, pseudocode, datasets, code, model cards, logs, environment details, or ablation notebooks.
  • Keep essential evidence in the paper whenever space allows because reviewers are not required to read supplementary material.
  • Put optional evidence in the Technical Appendix or ZIP, respecting the current size and format limit. IJCAI-ECAI 2026 allowed up to 50MB in PDF or ZIP form.
  • Anonymize repository paths, user names, institutions, license headers, model checkpoints, data provenance, and notebook metadata.
  • Include a minimal run map: environment, dependencies, hardware, commands, expected outputs, runtime, seeds, and known limitations.
  • For proprietary or restricted data/code, explain why it cannot be shared and provide enough detail for in-principle reproduction.

Evidence by claim type

IJCAI usually has no separate artifact-evaluation badge, so the artifact's job is to move the reproducibility rating toward convincing and to pre-empt a broad PC's doubt. Match the package to the claim.

Claim Artifact that convinces an IJCAI reviewer Weak substitute to avoid
New search/planning algorithm Runnable solver, instance generator, seeds, time/memory limits A results CSV with no way to regenerate it
Theoretical guarantee Full proofs, assumption list, citations to formal tools "Proof omitted for space" with no appendix
Multi-agent protocol Simulator, opponent policies, randomization seeds Screenshots of one run
Learning result Code, environment file, configs, compute and runtime Final-number table only
Dataset Datasheet, license, controlled-access path Vague "available on request"

Worked vignette: packaging a SAT-solver paper

A SAT/CSP paper claims a new restart heuristic wins on hard industrial instances. Strong package: the solver binary or source, the exact instance set or a deterministic generator, solver and compiler versions, per-instance runtimes with the timeout stated, and a run map showing one command that reproduces the cactus plot. Anonymize the repository name, license headers, and any cluster paths. This lets a skeptical constraint-reasoning reviewer re-run a sample and raises the rating from credible to convincing without needing a badge track.

Reviewer pushback and the venue-specific fix

  • "Cannot regenerate the benchmark instances." Ship a generator plus seeds, not just outputs.
  • "Artifact leaks author identity." Scrub paths, license headers, checkpoint names, and notebook metadata before the full-paper deadline; there is no late re-upload.
  • "Restricted data blocks reproduction." Document the legal barrier and give enough protocol for in-principle reproduction rather than implying a release you cannot deliver.

Output format

[Artifact role] paper evidence / supplement / post-acceptance release
[Contents] <proofs/code/data/models/logs/docs>
[Anonymity risks] <paths/licenses/metadata/URLs>
[Reproducibility claim] convincing / credible / weak
[Fixes before upload] <ordered list>
Info
Category Development
Name ijcai-artifact-evaluation
Version v20260724
Size 3.66KB
Updated At 2026-07-28
Language