Fix HF dataset handle typo and rename LICENCE.txt to LICENSE

- Correct Hugging Face dataset URL from 'Yuma-Ichikawsa' to
  'Yuma-Ichikawa' (17 occurrences across README, docs, data/*, scripts).
- Rename LICENCE.txt -> LICENSE so GitHub's licensee and PyPI license
  classifier can auto-detect the license. License terms are unchanged.
- Update pyproject.toml (license.file, sdist include) and README links
  to the new filename.
- Label the license as BSD-3-Clause-Clear in README and CITATION.cff;
  the text already matched the BSD-3-Clause-Clear SPDX template (the
  'NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS' clause
  distinguishes it from plain BSD-3-Clause).

Made-with: Cursor

Author: Yuma Ichikawa

CITATION.cff

@@ -8,7 +8,7 @@ authors:
     given-names: Yamato
 repository-code: "https://github.com/Yuma-Ichikawa/QQA4CO"
 url: "https://github.com/Yuma-Ichikawa/QQA4CO"
-license: BSD-3-Clause
+license: BSD-3-Clause-Clear
 version: 0.5.0
 date-released: 2026-04-19
 doi: 10.5281/zenodo.19648231

LICENCE.txt LICENSELICENCE.txt renamed to LICENSE

@@ -16,19 +16,19 @@ with earlier QQA4CO releases (``import qqa``).
 <p align="center">
   <a href="https://pypi.org/project/qqa/"><img src="https://img.shields.io/pypi/v/qqa.svg?logo=pypi&logoColor=white&label=PyPI" alt="PyPI version"></a>
   <a href="https://pypi.org/project/qqa/"><img src="https://img.shields.io/pypi/pyversions/qqa.svg?logo=python&logoColor=white" alt="Python versions"></a>
-  <a href="https://github.com/Yuma-Ichikawa/QQA4CO/blob/main/LICENCE.txt"><img src="https://img.shields.io/pypi/l/qqa.svg" alt="License"></a>
+  <a href="https://github.com/Yuma-Ichikawa/QQA4CO/blob/main/LICENSE"><img src="https://img.shields.io/pypi/l/qqa.svg" alt="License"></a>
   <a href="https://github.com/Yuma-Ichikawa/QQA4CO/actions/workflows/ci.yml"><img src="https://github.com/Yuma-Ichikawa/QQA4CO/actions/workflows/ci.yml/badge.svg" alt="CI"></a>
   <a href="https://yuma-ichikawa.github.io/QQA4CO/"><img src="https://img.shields.io/badge/docs-mkdocs--material-blue?logo=materialformkdocs&logoColor=white" alt="Documentation"></a>
   <a href="https://github.com/Yuma-Ichikawa/QQA4CO/discussions"><img src="https://img.shields.io/github/discussions/Yuma-Ichikawa/QQA4CO?logo=github&label=Discussions" alt="GitHub Discussions"></a>
   <a href="https://codecov.io/gh/Yuma-Ichikawa/QQA4CO"><img src="https://codecov.io/gh/Yuma-Ichikawa/QQA4CO/branch/main/graph/badge.svg" alt="Coverage"></a>
   <a href="https://doi.org/10.5281/zenodo.19648231"><img src="https://img.shields.io/badge/DOI-10.5281%2Fzenodo.19648231-1f6feb?logo=doi&logoColor=white" alt="DOI"></a>
-  <a href="https://huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-Yuma--Ichikawsa%2Fqqa4co--bench-yellow" alt="Hugging Face dataset"></a>
+  <a href="https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-Yuma--Ichikawsa%2Fqqa4co--bench-yellow" alt="Hugging Face dataset"></a>
 </p>
 
 <p align="center">
   <b>Benchmark data &nbsp;·&nbsp;</b>
-  <a href="https://huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench">
-    <code>huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench</code>
+  <a href="https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench">
+    <code>huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench</code>
   </a>
   <br>
   <sub>DISCS (NeurIPS 2023) + MaxCut G-set (Helmberg & Rendl 2000) + Graph Coloring (COLOR) + MIS on d-regular random graphs (PQQA §5.1) + 3D Edwards-Anderson spin glass + Balanced k-way partition — one HF dataset, <code>make bench-all-setup</code> pulls everything.</sub>
@@ -409,7 +409,7 @@ Run `qqa <command> --help` for the full option list.
 
 Every benchmark instance lives on the Hugging Face Hub:
 
-> **Dataset:** [`huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench)
+> **Dataset:** [`huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench)
 > &nbsp;&nbsp;·&nbsp;&nbsp; DISCS (MaxCut / MIS / MaxClique / NormCut) +
 > **MaxCut G-set (Helmberg & Rendl 2000, 71 graphs G1-G67 + G70/72/77/81)** +
 > Graph Coloring (COLOR) + MIS on d-regular random graphs (PQQA §5.1) +
@@ -751,7 +751,8 @@ Issues and pull requests are welcome. See
 
 ## License
 
-BSD-3-Clause — see [`LICENCE.txt`](LICENCE.txt).
+BSD-3-Clause-Clear (BSD-3-Clause with an explicit no-patent-grant
+clause) — see [`LICENSE`](LICENSE).
 
 ## Cite
 

README.md

@@ -37,6 +37,6 @@ Everything below `.gitignore` is re-generated locally by:
 python scripts/generate_coloring_instances.py
 ```
 
-Upstream distribution: `Yuma-Ichikawsa/qqa4co-bench` on the Hugging Face
+Upstream distribution: `Yuma-Ichikawa/qqa4co-bench` on the Hugging Face
 Hub (same repo as DISCS; see `data/discs/README.md` for credentials /
 fallbacks).

data/coloring/README.md

@@ -36,7 +36,7 @@ make bench-discs SUITE=mis-satlib BACKEND=qqa DEVICE=cuda
 That is it. The setup script will:
 
 1. **Download** the prebuilt dataset from the Hugging Face Hub
-   (`Yuma-Ichikawsa/qqa4co-bench`, override with `DISCS_HF_REPO_ID=...`) —
+   (`Yuma-Ichikawa/qqa4co-bench`, override with `DISCS_HF_REPO_ID=...`) —
    primary source, free, no auth required.
 2. **Or fall back** to the original Google Drive tarball
    (`DISCS-DATA.tar.gz`, ~6.7 GB) and extract just the `DISCS-DATA/sco/`

data/discs/README.md

@@ -41,5 +41,5 @@ against this published ground-state reference when available.
 python scripts/generate_ea3d_instances.py
 ```
 
-Upstream distribution: `Yuma-Ichikawsa/qqa4co-bench` on the Hugging Face
+Upstream distribution: `Yuma-Ichikawa/qqa4co-bench` on the Hugging Face
 Hub.

data/ea3d/README.md

@@ -1,5 +1,5 @@
 # The actual Gset payload (30 MB) lives on Hugging Face
-# (`Yuma-Ichikawsa/qqa4co-bench` under `gset/`). Pull it with
+# (`Yuma-Ichikawa/qqa4co-bench` under `gset/`). Pull it with
 # `make bench-all-setup` or `./scripts/setup_benchmarks.sh --only gset`.
 # The raw Stanford text files downloaded by
 # `scripts/fetch_gset_data.py` land under `raw/` and are likewise

data/gset/.gitignore

@@ -1,7 +1,7 @@
 # MaxCut — G-set benchmark
 
 **71 graphs**, best-known cuts tracked, hosted on
-[`Yuma-Ichikawsa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench)
+[`Yuma-Ichikawa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench)
 under `gset/`.
 
 | size               | instances            | typical n, m                                 |

data/gset/README.md

@@ -40,5 +40,5 @@ solver benchmark. We ship the `n = 10^4` variant here (covers both
 the Hugging Face Hub mirror stays lean. Reinstate it by passing
 `--nodes 1000000` to `scripts/generate_rrg_instances.py` if needed.
 
-Upstream distribution: `Yuma-Ichikawsa/qqa4co-bench` on the Hugging Face
+Upstream distribution: `Yuma-Ichikawa/qqa4co-bench` on the Hugging Face
 Hub.

data/mis-rrg/README.md

@@ -6,7 +6,7 @@ No edits to the repo or knowledge of its internals are required.
 
 Every benchmark instance lives on the Hugging Face Hub:
 
-> **[`huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawsa/qqa4co-bench)**
+> **[`huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench`](https://huggingface.co/datasets/Yuma-Ichikawa/qqa4co-bench)**
 
 The dataset bundles the [DISCS](https://arxiv.org/abs/2311.04730) CO
 benchmarks (NeurIPS 2023), the **MaxCut G-set** superset (71 graphs,