跳到主要内容
知仓学习社ZHICANG

wacv-reproducibility

Use when strengthening the reproducibility of a WACV paper, covering the recipe ledger for constraint-aware systems, benchmark and split hygiene, se…

不碰外部(只输出文字)无严重或高危命中brycewang-stanford/Awesome-Journal-Skills

它会碰到什么

扫了多少1 个文本文件,4 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

WACV Reproducibility

Use this to make a WACV result checkable — by a reviewer now and by you at the Round 2

resubmission. WACV's applications framing raises the bar in one direction (a systems claim

must be reproducible as deployed), and the two-round model adds a second (paper and

artifact must not drift between rounds). Facts are the WACV 2026/2027 cycles as read on

2026-07-09.

The recipe ledger

Keep one ledger that regenerates every reported number, so the body, the supplement, and the

artifact cannot diverge:

| Ledger entry | Why WACV cares |

|---|---|

| Exact data splits and preprocessing | Applications datasets are often custom; a hidden split invalidates a comparison |

| Seeds (and sessions/devices for field work) | Reviewers distrust single hero runs |

| Hyperparameters per reported row | Lets a reviewer see the comparison was matched |

| Device, power meter, and measurement method | An applications latency/wattage claim is only reproducible if the rig is named |

| Baseline re-tuning under your constraint | Proves the comparison was fair, not defaults-vs-yours |

| Script → figure/table mapping | So a Round 2 reviewer confirms nothing changed silently |

Constraint-aware reproducibility

An Applications-track claim ("2 W, sub-10-lux, on device D") is not reproducible from

accuracy alone. Record how the constraint was measured — the meter, the device firmware, the

ambient condition — so a reviewer or a future reader can reproduce the constraint, not just

the metric. A number without its measurement rig is a claim, not evidence.

Repro smoke check before submission (and again before the R2 resubmission):
  1. Fresh checkout → run the pipeline for one reported row end to end.
  2. Confirm the produced number matches the paper within the stated spread.
  3. Diff the artifact's claims against the current paper's claims — zero drift allowed.
  4. Strip identity from the anonymous package (see wacv-artifact-evaluation).

Seed and session honesty

Report variance over seeds, and for deployed/field systems over repeated sessions or

devices. Do not report the best of many runs as "the" result. If a gap sits within the

spread, say so — an honest small margin survives review better than an inflated one that a

reviewer's own reproduction contradicts.

Sync across the two rounds

The Revise-and-Resubmit lap is where reproducibility quietly breaks: authors change an

experiment in the paper but not in the artifact, or vice versa. After every revision, re-run

the smoke check and re-diff the artifact against the paper. A Round 2 reviewer re-reading a

revised submission should find the package and the paper telling one story.

Reverify each cycle

  • Whether the current guidelines request a reproducibility statement or checklist.
  • Data-release and licensing rules for any dataset used as evidence.
  • Supplementary size/format caps that constrain what you can ship (待核实 for 2026).

Output format

[Recipe ledger] regenerates every reported number: yes/no
[Constraint rig] device/meter/condition recorded for systems claims: yes/no
[Seeds/sessions] variance reported honestly: yes/no
[Baselines] re-tuned under your constraint and logged: yes/no
[Round sync] artifact matches current paper (zero drift): yes/no
[Gap] <the number a reviewer could not currently reproduce>

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。