| --- |
| license: odc-by |
| language: |
| - hy |
| task_categories: |
| - text-generation |
| tags: |
| - arxiv:2609.03350 |
| - armenian |
| - pretraining |
| - news |
| - deduplicated |
| - decontaminated |
| size_categories: |
| - 1M<n<10M |
| pretty_name: ArmWeb |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train/* |
| - split: validation |
| path: data/validation/* |
| - split: test_iid |
| path: data/test_iid/* |
| - split: test_tail |
| path: data/test_tail/* |
| --- |
| |
| # ArmWeb |
|
|
| **ArmWeb** is a curated Armenian news corpus for language-model pretraining: |
| **4.37M documents / 11 GB / 3.3B Gemma-4 tokens** (1.15B tokens in the 32K |
| SentencePiece tokenizer used for the small-scale ablations) of deduplicated, decontaminated Eastern and |
| Western Armenian text with document-level provenance (URL, outlet, topic, |
| publication date). To our knowledge it is the first and largest open |
| pretraining corpus *built specifically for* Armenian — existing Armenian text |
| at scale exists only as slices of multilingual web crawls with no |
| Armenian-specific curation. |
|
|
| Paper: [*From Zero to Hero: An Open LLM Ecosystem for Armenian*](https://arxiv.org/abs/2609.03350) |
| (arXiv:2609.03350). Sister releases: [COPA-AI/armstem](https://huggingface.co/datasets/COPA-AI/armstem) |
| and [COPA-AI/arm-gemma-e4b](https://huggingface.co/COPA-AI/arm-gemma-e4b). |
|
|
| ## Why another Armenian corpus? |
|
|
| Because the existing ones are contaminated and duplicated. Scanning the |
| Armenian slices of public corpora against ten Armenian benchmarks (13-gram |
| overlap, normalized text): |
|
|
| | Corpus | Docs | Gemma-4 tokens | Benchmark-contaminated | |
| |---|---|---|---| |
| | **ArmWeb (this release)** | 4.46M | 3.3B | **3.3% → removed** | |
| | CulturaX-hy | 2.96M | 4.5B | 7.9% | |
| | HPLT-v2-hy | 3.60M | 5.8B | 10.9% | |
| | FineWeb-2-hy | 1.76M | 2.3B | 17.4% | |
|
|
| Token sizes re-tokenize each corpus as distributed with the Gemma-4 |
| vocabulary (ArmWeb as released), so they are comparable: ArmWeb has the most |
| documents but, being news, the least text of the three large corpora. |
|
|
| FineWeb-2's Armenian *training* split overlaps its own *test* split. Any |
| evaluation of Armenian-trained models without decontamination is inflated. |
| ArmWeb ships with its contamination **removed** and the scan code released. |
|
|
| ArmWeb is also complementary to the crawls, not redundant with them: in |
| controlled 410M ablations it is ~10% better bits-per-byte on held-out news, |
| and the **union** of ArmWeb + CulturaX beats every single corpus on the |
| panel mean (0.532 vs 0.545 bpb for the best single corpus) and is within |
| 0.007 bpb of the best on every panel — a lead that widens at 1.3B (see |
| paper, Appendix). |
|
|
| ## Contents |
|
|
| - **Source**: a single-operator crawl of public Armenian news sites, |
| 2011–2026, stored as a structured database (not raw HTML — near-zero |
| boilerplate by construction). |
| - **Splits**: train (4.31M docs) / validation (20K) / test_iid (20K) / |
| test_tail (20K; the final two months, for temporal generalization). |
| Splits are stratified by outlet×month; deduplication ran **globally before |
| splitting**, and three leakage gates are verified: zero exact cross-split |
| collisions and near-duplicate rates ≤0.045% (val), 0.010% (test_iid), |
| 0.005% (test_tail) run as hard assertions in the release build, and a |
| third gate counts cross-split shared paragraphs of ≥13 tokens: 30 (val), |
| 63 (test_iid), 10 (test_tail) per 20K-document split. |
| - **Fields**: `id`, `text` (NFC-normalized, otherwise verbatim), `source` |
| (outlet), `url`, `topic`, `post_date` (publication), `scrape_date` |
| (crawl), `dedup_cluster_id`, `cluster_size` (size of the near-duplicate |
| cluster this document represents), `split`. Author names are not |
| released. |
|
|
| ## Pipeline (fully documented in the paper) |
|
|
| | Stage | Documents | Δ | |
| |---|---|---| |
| | Extracted | 5,918,811 | — | |
| | Language ID (GlotLID, hye/hyw) | 5,817,343 | −1.7% | |
| | Exact dedup (xxh128, keep-longest) | 5,436,984 | −6.5% | |
| | MinHash dedup (see below) | 4,515,497 | −16.9% | |
| | Repeated-paragraph removal | 4,515,484 | −0.0% | |
| | Splits held out (val/test_iid/test_tail, 20K each) | 4,455,484 | −60K | |
| | Benchmark decontamination (train side) | 4,308,383 | −3.3% | |
|
|
| The dedup engine is cross-checked twice: the reference datasketch library, |
| run with the identical recipe on a 1% sample, finds 449 in-sample |
| duplicates of which the engine had already flagged 95.8%; NVIDIA |
| NeMo-Curator at matched LSH geometry removes 23.5% vs our 22.4% on the |
| full corpus with 99.2% per-document agreement on a matched-scope sample, |
| disagreements confined to below-threshold borderline pairs (paper, |
| Appendix). The identical recipe applied to a Russian sister collection |
| from the same crawler removes only 0.9% of documents, so the high Armenian |
| removal rate reflects real news syndication, not an aggressive pipeline. |
|
|
| MinHash: word 5-gram shingles on an aggressive NFKC "signature view" |
| (Armenian ligature folding, punctuation stripping, digit-zeroing), 112 |
| permutations, 14 bands × 8 rows (Jaccard ≈ 0.72). The lower-than-standard |
| threshold is deliberate: news syndication produces true reprints at far lower |
| Jaccard than web duplicates, and 0.8-threshold recipes miss most of them. |
| Decontamination: 13-gram overlap against ten Armenian evaluation sets |
| (Belebele, INCLUDE, HellaSwag-hy, MultiBLiMP, SIB-200, SynDARin, LR-Sum, |
| the FineWeb-2-hy test split, hyWiki eval, FLORES-200), 147,101 documents |
| removed. m-MMLU-hy and ARC-hy were not decontamination targets; a post-hoc |
| scan found **zero** of the 4.31M training documents share any 13-gram |
| with either benchmark. |
|
|
| ## License and attribution |
|
|
| The **compilation** (selection, cleaning, deduplication, metadata, splits) is |
| released under **ODC-BY 1.0**. The crawl honored the sites' crawling rules, |
| including robots.txt directives. The underlying article texts remain the |
| copyright of their respective publishers; per-document `url` and `source` |
| fields preserve attribution. Author bylines are removed; a PII scan (942 |
| e-mail addresses in 782 documents, 8,971 documents with phone-number-like |
| strings, overwhelmingly newsroom and institutional contact lines) ships |
| with the corpus. The corpus is released for research use, |
| consistent with text-and-data-mining practice for web-derived pretraining |
| corpora (C4, OSCAR, FineWeb). If you are a rights holder and want content |
| removed, open a discussion on this repository. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{arakelyan2026armweb, |
| title = {From Zero to Hero: An Open LLM Ecosystem for Armenian}, |
| author = {Arakelyan, Erik and Avetisyan, Khatun and Davtyan, Meri and Grigoryan, Heghine and Khachatryan, Nane and Shahsuvaryan, Hayk and Sergoyan, Henrik and Martirosyan, Vahan}, |
| year = {2026}, |
| journal = {arXiv preprint arXiv:2609.03350} |
| } |
| ``` |
|
|
