anonymous-md/ProseOnlyRepair_Codes

ProseOnlyRepair — Evaluation Analysis Scripts

Anonymized evaluation/analysis scripts that reproduce the tables and figures in the Repair-First paper (under double-blind review).

Contents

File	Purpose
build_paper_tables.py	Headline tables (per-task accuracy, Paloma BPB, repair deltas)
build_8variant_analysis.py	8-variant repair-effect-by-tier analysis (POST-only excluded)
build_12variant_analysis.py	12-variant superset including POST-only (used in appendix)
make_paper_figures.py	Regenerates Figures 1 and 2 from eval JSONs
requirements.txt	Python dependencies (lm-evaluation-harness 0.4.12, datasets <4.0, etc.)

Variant naming

Each evaluation result directory follows {cluster}_{tier}_new[_repaired[_upsampled]]_results:

Token	Meaning
clusterA_	Pretrained on Cluster A (anonymous identifier)
clusterB_	Pretrained on Cluster B (anonymous identifier)
_lq / _mq / _hq	Low / Medium / High quality CommonCrawl tier
_new	PRE: pre-repair baseline
_new_repaired	POST: post-repair, token budget held by truncation
_new_repaired_upsampled	POST+UP: post-repair + upsampled to original token budget

How to use

pip install -r requirements.txt
# Place evaluation result JSONs under ./eval_results/{prose,paloma}/
python3 build_paper_tables.py
python3 build_8variant_analysis.py
python3 build_12variant_analysis.py
python3 make_paper_figures.py

The accompanying evaluation result JSONs (12 variants × prose + paloma suites) are released in the paper's supplementary materials zip.

Notes

• All scripts are CPU-only Python and require no GPU.
• Scripts are deterministic: identical inputs → identical outputs.
• The 28-task prose suite + 11-corpus Paloma BPB panel are evaluated with lm-evaluation-harness==0.4.12 (vLLM backend).
• Decoding: greedy, max-len 256 except CoQA/SQuADv2 (512).

This release is anonymous for double-blind review and will be re-released with author and affiliation metadata after the review period.