--- license: other license_name: arxiv-nonexclusive license_link: https://arxiv.org/help/license task_categories: - text-generation - feature-extraction language: - en tags: - mathematics - number-theory - arxiv - latex - scientific pretty_name: arXiv Number Theory Papers size_categories: - n<1K --- # arXiv Number Theory Papers A focused dataset of recent `math.NT` (number theory) papers from arXiv, prepared for language-model training and research. Companion to `math-papers-10m`, but narrowed to a single subfield for dense topical coverage. ## Summary - **Category:** `math.NT` (primary) - **Total papers:** 500 - **Total body tokens (cl100k_base):** 16,400,635 - **Source:** arXiv (https://arxiv.org), via the `arxiv` Python client + content endpoints (`/html/`, `/e-print/`, `/pdf/`) - **Generated:** 2026-04-11 - **License:** Papers are redistributed under arXiv's non-exclusive license to distribute. See https://arxiv.org/help/license. Cite the original authors. ## Contents Each batch is a Parquet file under `data/`: ``` data/batch-0001.parquet data/batch-0002.parquet ... ``` Per-row schema: | field | type | description | | --- | --- | --- | | `arxiv_id` | string | Canonical arXiv identifier | | `title` | string | Paper title | | `authors` | list[string] | Author names | | `abstract` | string | Paper abstract | | `primary_category` | string | Always `math.NT` (primary category) | | `categories` | list[string] | All arXiv subject tags (may include cross-listings) | | `published` | string | ISO-8601 submission timestamp | | `updated` | string | ISO-8601 last-updated timestamp | | `abs_url` | string | arXiv abstract URL | | `pdf_url` | string | arXiv PDF URL | | `body` | string | Cleaned body text (math preserved as LaTeX in `$...$`) | | `body_chars` | int | Character length of `body` | | `body_tokens` | int | Token count via tiktoken `cl100k_base` | | `extraction_method` | string | `html`, `pylatexenc`, or `pymupdf` | | `has_tex` | bool | Whether original .tex tarball is attached | | `has_pdf` | bool | Whether original PDF is attached | | `tex_bytes_len` | int | Size of .tex tarball on the repo | | `pdf_bytes_len` | int | Size of PDF on the repo | Raw source artifacts live alongside the Parquet data: ``` sources/tex/.tar.gz sources/pdf/.pdf ``` ## Primary-category breakdown | Category | Papers | Share | | --- | --- | --- | | math.NT | 361 | 72.2% | | math.AG | 42 | 8.4% | | math.CO | 34 | 6.8% | | math.RT | 13 | 2.6% | | math.DS | 12 | 2.4% | | math.LO | 5 | 1.0% | | cs.IT | 3 | 0.6% | | math.SP | 3 | 0.6% | | math.GT | 3 | 0.6% | | math.PR | 3 | 0.6% | | hep-th | 2 | 0.4% | | math.AC | 2 | 0.4% | | cs.CR | 2 | 0.4% | | math.KT | 2 | 0.4% | | math-ph | 2 | 0.4% | | math.CA | 2 | 0.4% | | cs.MS | 2 | 0.4% | | math.HO | 1 | 0.2% | | math.CV | 1 | 0.2% | | cs.FL | 1 | 0.2% | | quant-ph | 1 | 0.2% | | math.QA | 1 | 0.2% | | math.MG | 1 | 0.2% | | math.FA | 1 | 0.2% | ## Year distribution (submission year) | Year | Papers | | --- | --- | | 2026 | 500 | ## Methodology 1. **Metadata:** Fetched via the `arxiv` Python client (ToS-compliant 3.1s delay, retries on 429/503). Query: `cat:math.NT`, sorted by submission date descending. 2. **Body extraction cascade (per paper):** - **HTML-first:** `arxiv.org/html/` is fetched and parsed with BeautifulSoup. MathML `` elements are replaced with their LaTeX source (from the `` child) so each equation appears once, not duplicated as both Unicode rendering and LaTeX source. - **pylatexenc fallback:** If HTML is unavailable, the `/e-print/` tarball is unpacked and the main .tex is converted via pylatexenc with math preserved in delimited form. - **pymupdf fallback:** Last resort — body text extracted from the PDF via PyMuPDF (math renders as plaintext garbage but guarantees coverage). 3. **Body filter:** Reject bodies below 1000 chars or 300 tokens. 4. **Token count:** `tiktoken.get_encoding("cl100k_base")`. 5. **Artifacts:** Every paper gets its raw `.tar.gz` e-print and original `.pdf` uploaded alongside the Parquet row. ## Extraction method breakdown - html: 450 - pylatexenc: 46 - pymupdf: 4 ## Caveats - Bodies retain references to figures/tables; figures themselves are not extracted. - Bibliographies are stripped pre-extraction. - Math coverage depends on extractor: HTML produces the cleanest output because it uses the LaTeXML-generated LaTeX source directly; pylatexenc is a close second; pymupdf (PDF fallback) produces the weakest math. - Date range reflects the most recent papers on arXiv at the time of scraping (see "Year distribution" above). ## Provenance - Generated by `scripts/08_nt_dataset.py` in the math-papers-pipeline repo. - Reproducible: same arXiv query + fixed sort order + fixed batch size.