cav-experiments
From the author
Use when designing or auditing a CAV (Computer Aided Verification) empirical evaluation, covering standard benchmark sets (SV-COMP/SMT-COMP/HWMCC/VNN-COMP), fair baseline solvers with pinned versions and equal resource limits, timeout-dominated comparisons, soundness cross-checks and proof witnesses, cactus/scatter reporting, and matching evidence to the shape of each verification claim.
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cav-experiments -a claude-code
Installs to .claude/skills/cav-experiments/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Similar skills
Closest to this one by what they do and when they are used.
- cav-submissionbrycewang-stanford/Awesome-Journal-SkillsUse when auditing a CAV (Computer Aided Verification) submission for portal readiness, covering the four submission categories (Regular / Short Tool / Short Application / Industrial Experience & Case Studies), the LNCS page limits, the per-category anonymization matrix, the artifact-intent declaration, and desk-reject triage before the AoE paper deadline.Science★ 1.3K
- cav-workflowbrycewang-stanford/Awesome-Journal-SkillsUse when planning a CAV (Computer Aided Verification) project timeline from venue and category selection through submission, the two-stage review with early reject and rebuttal, artifact evaluation by the AEC, and the LNCS open-access camera-ready, with backward-planning offsets for a verification-tool paper and honest handling of the single-annual-deadline cycle.Productivity★ 1.3K
- eccv-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the experimental program of an ECCV paper — benchmark selection that survives a September conference, matched-substrate baseline fairness in the foundation-model era, ablations that isolate the claimed mechanism, qualitative failure evidence, and run sequencing toward a March freeze.Science★ 1.3K
- wacv-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing WACV experiments, covering Applications-track systems evidence (latency, power, robustness under real constraints) versus Algorithms-track matched-baseline novelty, comparative assessment under the deployed condition, uncertainty over seeds and sessions, ablations, and evidence that survives the two-round review.DevOps★ 1.3K
- cav-writing-stylebrycewang-stanford/Awesome-Journal-SkillsUse when revising a CAV (Computer Aided Verification) paper for a precise verification contribution on the first page, an explicit soundness/completeness statement, theorem-and-proof discipline in the LNCS page budget, fair benchmark claims, honest scope and limits, and double-blind wording for the anonymized categories.Writing★ 1.3K
- cvpr-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the experimental program of a CVPR paper, covering benchmark and baseline selection under matched-compute fairness, the ablation study reviewers treat as mandatory, qualitative and failure-case evidence, efficiency metrics tied to the Compute Reporting Form, and generalization tests beyond a single dataset.Testing★ 1.3K
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