license: cc-by-4.0
tags:
- retrieval
- mathematics
- embeddings
pretty_name: RecipeMatching evaluation artifacts
RecipeMatching evaluation artifacts
Per-query rank dumps and embedding caches behind the paper Recipe-Matching, Not Equivalence (Ali Habibullah, Mohammad Alshiekh, Yazan Alshoibi, Salman Khan and Naeemullah Khan, 2026). Code, data and results: https://github.com/KAUST-Academy/recipe-matching-not-equivalence.
These files are too large for the GitHub repository. Every number in the paper is already stored there as a result JSON; the files here are what the analysis scripts need in order to recompute the confidence intervals and the style analyses without re-running any model.
Contents
| Path | Files | Size | What it is |
|---|---|---|---|
results/ranks/*.ranks.jsonl |
891 | 1.8 GB | One JSON line per query: its id and the rank of its gold document (fields vary by evaluation, e.g. gold_rank, gold_sim, top10_ids). Written by scripts/eval_retrieve.py --dump-ranks, scripts/eval_crosslingual.py, scripts/eval_bm25.py and scripts/colbert_eval.py. The repository's results/ranks/*.summary.json files are their aggregates. |
emb_cache/*.npz |
16 | 4.4 GB | MathNet-Retrieve document (117,088) and query (15,000) embeddings of eight fine-tuned checkpoints, arrays ids and emb: ctrl-cas-6145, ctrl-llm-6145, dose-paraphrase-6145, dose-style-6145, dose-unrelated-6145, fact-d4casnegs-6145-s42, fact-d4llmnegs-6145-s42 and fact-d4llmnegsfull-6145-s42 (training records in models/<name>/run_config.json of the repository). |
upstream_versions/ |
2 | small | The Hugging Face revision of every base model and dataset the experiments downloaded, recorded on 2026-09-28, and the commit of the MIRB code. |
Use
Clone the GitHub repository, then place the files where the scripts expect them:
hf download KAUSTAcademy/RecipeMatching_eval-artifacts --repo-type dataset --local-dir artifacts
cp artifacts/results/ranks/*.ranks.jsonl results/ranks/
mkdir -p .emb_cache && cp artifacts/emb_cache/*.npz .emb_cache/
The bootstrap, difference-in-differences and slice scripts (for example scripts/bootstrap_stats.py,
scripts/dose_bootstrap.py, scripts/reference_control_did.py, scripts/xling_slice_analysis.py and
scripts/samelang_verdict.py) read the rank dumps; scripts/style_probe.py, scripts/style_within_class.py
and scripts/analyze_hits.py read the embeddings.
Citation
@misc{habibullah2026recipematchingequivalence,
title={Recipe-Matching, Not Equivalence},
author={Ali Habibullah and Mohammad Alshiekh and Yazan Alshoibi and Salman Khan and Naeemullah Khan},
year={2026},
eprint={2609.31927},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2609.31927},
}