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name: uist-artifact-evaluation description: Use when packaging the artifacts behind a UIST paper — code, toolkits, hardware design files, and datasets — first as anonymous review-time evidence that the system is real, then as a public release engineered for reuse, in a venue with no formal badge committee doing the checking for you.

UIST Artifact Evaluation

UIST has no artifact-evaluation committee or badge track (none was found for the 2026 cycle — 待核实 each year); the CFP-level instrument of proof is the video figure. That absence raises rather than lowers the packaging bar: your artifacts are judged twice, informally — at review time as evidence the system exists as claimed, and after publication as infrastructure other builders adopt. Nobody will certify either; both simply succeed or fail.

What counts as the artifact, by paper type

Paper type	Review-time artifact	Reuse-time artifact
Interaction technique	Reference implementation + demo scene	Portable library with the technique isolated
Toolkit / authoring system	Runnable toolkit + the example apps from the paper	Documented API, tutorials, package registry entry
Hardware / fabrication	Design files, firmware, BOM, assembly photos	Fab-ready files + sourcing notes + calibration guide
Sensing / recognition pipeline	Trained models + capture data + eval harness	Dataset with collection protocol + retraining scripts
Human-AI / LLM system	Prompts, orchestration code, pinned model IDs, logged transcripts	Same, plus cost and drift notes

Review-time packaging: the five-minute skeptic

A reviewer gives your supplement five minutes, anonymously, on a machine you don't control. Optimize for that reader:

• One README at the archive root: what this is, which paper section each directory backs, and one command (or one video) per claim.
• Prefer a recorded run alongside the code for anything with hardware, drivers, or GPU dependencies — reviewers cannot rebuild your rig, so show the harness producing the paper's numbers.
• Pin everything (lockfiles, container image digests, model checkpoints); "latest" is a broken artifact by review week.
• Anonymize as strictly as the PDF: repository history, notebook authorship cells, hardcoded home paths, calibration files named after lab members (see uist-submission for the sweep).

supplement.zip
├── README.md              # claim → artifact map; 5-minute quickstart
├── technique/             # core implementation, pinned deps
├── hardware/              # schematics, PCB, STL/STEP, BOM.csv, firmware/
├── eval/                  # harness + raw logs behind Tables 1-2
│   └── rerun.sh           # regenerates the paper's numbers from logs
├── media/                 # per-claim capture clips (beyond the video figure)
└── LICENSES.md            # third-party components and their terms

Release-time packaging: engineering for strangers

At camera-ready (see uist-camera-ready), the audience flips from three skeptics to an open-ended stream of builders:

1. De-anonymize deliberately — publish to the real org, restore attribution, add the paper citation and BibTeX to the README.
2. Cut a release tag matching the camera-ready ("as-published") so later development never orphans the paper's claims.
3. Choose licenses by artifact class: code (e.g. MIT/Apache-2.0), hardware designs (e.g. CERN-OHL), data (e.g. CC-BY) — one archive often needs all three, and institutional tech-transfer rules for hardware are worth checking early.
4. Archive beyond the repo: deposit the tagged release with a DOI service so the URL in the proceedings outlives your hosting choices.
5. State the support posture honestly in the README — "research prototype, issues welcome, no maintenance promised" is respectable; silence is not.

What the informal evaluators open first

Order the package for actual reading behavior:

1. README, thirty seconds. If the claim → artifact map is not visible without scrolling, the evaluation is over.
2. The media directory, two minutes. Clips of the harness producing the paper's numbers get watched; they are the highest-credibility artifact per byte, especially for hardware.
3. One quickstart command, two minutes. Whatever you name in the README as "run this" will be run in a fresh environment; test it in a container or a colleague's clean machine, not your dev box.
4. Source spot-checks. Reviewers grep for the mechanism the paper claims is novel; if the "self-calibrating controller" is a 30-line stub, the paper's credibility inverts. Never ship scaffolding that contradicts the prose.

Toolkit papers: adoption is the long evaluation

For toolkit and authoring-system contributions, the release is the deferred evaluation, and small engineering choices compound:

• Publish to the ecosystem's registry (pip/npm/crates/Arduino library manager) — installability is adoption's first filter.
• Ship the paper's example applications as runnable starters; they are the tutorials people actually read.
• Keep the API surface documented at the level of the paper's abstractions, so citations of the toolkit describe your concepts in your vocabulary.
• Track downstream uses; a "built with X" list is both maintenance motivation and the evidence base for the retrospective the venue's decade-scale memory eventually invites.

Hardware honesty

Physical artifacts cannot be uploaded, so their evidence standard is reconstruction: exact part numbers with sources, tolerances that matter, assembly sequence photos, firmware flashing instructions, and the calibration procedure with expected readings. A paper whose device only the authors can build has published a demo, not a contribution — reviewers from fabrication-heavy labs apply exactly that test (see uist-reproducibility for the replication ledger).

Output format

[Artifact class] technique / toolkit / hardware / pipeline / hybrid
[Review package] five-minute test passes? claim→artifact map complete?
[Anonymity] archive-level sweep clean?
[Release plan] tag · licenses (code/hardware/data) · DOI deposit · support posture
[Gap list] <artifacts named in the paper but absent from the package>