yogsoth-ai Leaderboard Harvesting
Purpose
Harvest structured performance data from leaderboard platforms (Papers With Code, benchmark-specific sites), survey papers, and official benchmark repositories. Produces deduplicated, provenance-tracked score collections.
Stages
Stage 1: Platform Scan
Identify and scrape all relevant leaderboard sources:
- Papers With Code task pages
- Benchmark-specific leaderboards (e.g., GLUE, ImageNet, WMT)
- GitHub benchmark repositories
- Survey papers with comprehensive comparison tables
Yield: List of leaderboard URLs + initial method counts per source.
Stage 2: Paper Extraction
For methods not covered by leaderboards, extract scores directly from papers:
- Original method papers (primary source)
- Ablation studies and follow-up papers
- Reproduction studies and benchmarking papers
Yield: Raw score tuples with paper provenance.
Stage 3: Cross-Validation
Compare scores across sources for the same method-dataset-metric triple:
- Flag discrepancies > 1 standard deviation
- Prefer primary sources when conflicts exist
- Note which scores come from official vs. unofficial implementations
Yield: Validated score set with confidence annotations.
Stage 4: Dedup and Merge
Consolidate all sources into a single canonical dataset:
- Resolve method name aliases
- Merge duplicate entries with provenance tracking
- Assign confidence levels based on source agreement
Yield: Unified performance dataset ready for analysis.
Minimum Yield
| Metric | Floor |
|---|---|
| Leaderboard sources checked | 3 |
| Methods with scores | 15 |
| Cross-validated score pairs | 10 |
| Deduplication conflicts resolved | 5 |
SOPs Used
- method-discovery (for finding methods on leaderboards)
- score-extraction (for paper-based extraction)
- discrepancy-identification (for cross-validation)
Available SOPs
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| discrepancy-identification | Compare same-method scores across sources, flag significant deviations |
| method-discovery | Identify all relevant methods via literature, leaderboards, citation chains |
| score-extraction | Extract (Task, Dataset, Metric, Score, Conditions) tuples from a paper |