pretty_name: DiBO Design-Bench Reproducibility Snapshot
tags:
- design-bench
- black-box-optimization
- offline-black-box-optimization
- reproducibility
- dibo
DiBO Design-Bench Reproducibility Snapshot
This repository contains the exact design_bench_data.zip snapshot used in
the experiments for Training Diffusion Language Models for Black-Box Optimization.
The artifact supports reproduction of the released DiBO training,
data-preparation, and evaluation workflows.
Scope
This repository is a DiBO reproducibility snapshot. It is not presented as the official, canonical, complete, or latest Design-Bench distribution.
Users reproducing the released DiBO experiments should use this snapshot. For upstream Design-Bench software, task definitions, and documentation, see Design-Bench. For a more comprehensive community-maintained/reference data mirror, see beckhamc/design_bench_data.
Comparison with the reference mirror
The snapshot was compared file-by-file with revision 79006c5105c6d0da75b2d9b599f31a5e74136778 of
beckhamc/design_bench_data. After removing the local archive's top-level
design_bench_data/ prefix:
- 244 file paths were shared;
- all 244 shared files were byte-identical;
- every shared file used by TFBind8, TFBind10, Ant Morphology, and D'Kitty Morphology was byte-identical;
- the local snapshot and the reference mirror differ in coverage.
The DiBO snapshot is smaller and does not contain every task or auxiliary file
in the more comprehensive reference mirror. See
SOURCE_COMPARISON.md for exact methodology,
task-level counts, local-only files, reference-only files, and hashes.
Important preprocessing note
design_bench_data.zip is not itself the final DiBO data/ directory.
Unzipping it does not directly produce all DiBO-specific task bundles,
relabeled morphology scores, prompt artifacts, reward statistics, or
normalization metadata. Use the released DiBO data-preparation pipeline and
follow data/README.md
and docs/installation.md.
Download
hf download zpointsun/DiBO-DesignBench-Snapshot design_bench_data.zip \
--repo-type dataset --revision v1.0.0 --local-dir data/downloads
python scripts/prepare_design_bench_data.py \
--archive data/downloads/design_bench_data.zip
Artifact details
- Archive:
design_bench_data.zip - Archive byte size: 142,923,783
- Archive SHA-256:
6a642d8b78f79ffb82ee6d7b73e2c4569c92e2f31a325cea32c4e7ef68e32e81 - ZIP entries: 261 (247 files and 14 directories)
- Uncompressed bytes: 593,018,567
The complete decompressed-member manifest is in FILE_MANIFEST.csv.
Citation
If you find DiBO helpful, please cite:
@article{sun2026training,
title={Training diffusion language models for black-box optimization},
author={Sun, Zipeng and Chen, Can and Yuan, Ye and Wu, Haolun and Gu, Jiayao and Pal, Christopher and Liu, Xue},
journal={arXiv preprint arXiv:2603.17919},
year={2026}
}