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RyanZhou168
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baseline-selector

Select GitHub-reproducible research baselines with venue-aware and reviewer-risk filtering.

52|1|Updated Jun 24, 2026
Search Tags:#research#academic#codex#reproducibility#experimentation#baselines
One-click install
npx skills add https://github.com/RyanZhou168/baseline-selector --skill baseline-selector
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: baseline-selector
Source: https://github.com/RyanZhou168/baseline-selector/tree/main
Command: npx skills add https://github.com/RyanZhou168/baseline-selector --skill baseline-selector

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) and examples (resource) components.

What problem does it solve?

This Skill solves the challenge of selecting a defensible, fair, and reproducible set of experimental baselines for research papers, ensuring your comparisons stand up to rigorous peer review.

Core Features & Use Cases

  • GitHub Reproducibility Gate: Automatically filters out papers that lack usable, non-empty, or runnable code repositories.
  • Venue-Aware Recommendations: Tailors baseline sets based on the specific target conference (e.g., ICML, NeurIPS, CVPR) and your available compute budget.
  • Reviewer-Risk Audit: Identifies missing classic anchors, recent SOTA, or simple baselines that reviewers are likely to demand.
  • Use Case: If you are preparing a submission for CVPR 2027 on 3D detection, use this Skill to generate a defensive baseline set that includes official benchmark methods, recent SOTA, and necessary ablations, while excluding non-reproducible papers.

Quick Start

Use the baseline-selector skill to choose baselines for my research idea on long-context multimodal retrieval targeting AAAI 2027 with a compute budget of 4x A100.

Frequently Asked Questions about baseline-selector

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I select reproducible research baselines for my experiment?▼

Select reproducible research baselines by validating candidate papers through a GitHub reproducibility gate that filters out methods lacking usable or runnable code repositories, ensuring fair and executable experimental comparisons.

What makes a baseline set defensible for peer review?▼

A defensible baseline set passes a reviewer-risk audit identifying missing classic anchors, recent SOTA, and simple baselines, while aligning with field-specific benchmarks, metrics, and reviewer expectations for rigorous peer review.

Can I tailor baseline recommendations to a specific conference and compute budget?▼

Yes, venue-aware recommendations tailor baseline sets to specific target conferences like ICML or CVPR while applying compute-aware filtering to match your available compute budget for experimental feasibility.

How do I prepare a defensive baseline set for a CVPR 3D detection paper?▼

Prepare a defensive baseline set for CVPR 3D detection by generating recommendations that include official benchmark methods, recent SOTA, and necessary ablations while excluding non-reproducible papers lacking runnable code repositories.

Why would my paper get rejected for missing simple baselines?▼

Papers risk rejection for missing simple baselines because reviewers demand them to contextualize performance gains; a reviewer-risk audit identifies missing simple baselines, classic anchors, and recent SOTA before submission.

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