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- README.md +258 -0
- en/checksum.sha256 +45 -0
- en/en1.0-0.jsonl.gz +3 -0
- en/en1.0-1.jsonl.gz +3 -0
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- fr/checksum.sha256 +20 -0
- fr/fr1.0-0.jsonl.gz +3 -0
- fr/fr1.0-1.jsonl.gz +3 -0
README.md
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---
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pretty_name: HALvest
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configs:
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- config_name: bg
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data_files: "bg/*.gz"
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- config_name: br
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data_files: "br/*.gz"
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- config_name: ca
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data_files: "ca/*.gz"
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- config_name: cs
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data_files: "cs/*.gz"
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- config_name: da
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data_files: "da/*.gz"
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- config_name: de
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data_files: "de/*.gz"
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- config_name: el
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data_files: "el/*.gz"
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- config_name: en
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data_files: "en/*.gz"
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- config_name: eo
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data_files: "eo/*.gz"
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- config_name: es
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data_files: "es/*.gz"
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- config_name: et
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data_files: "et/*.gz"
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- config_name: eu
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data_files: "eu/*.gz"
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- config_name: fa
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data_files: "fa/*.gz"
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- config_name: fi
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data_files: "fi/*.gz"
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- config_name: fr
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data_files: "fr/*.gz"
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- config_name: gl
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data_files: "gl/*.gz"
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- config_name: he
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data_files: "he/*.gz"
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- config_name: hr
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data_files: "hr/*.gz"
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- config_name: hu
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data_files: "hu/*.gz"
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- config_name: hy
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data_files: "hy/*.gz"
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- config_name: id
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data_files: "id/*.gz"
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- config_name: it
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data_files: "it/*.gz"
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- config_name: ko
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data_files: "ko/*.gz"
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- config_name: "no"
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data_files: "no/*.gz"
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- config_name: pl
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data_files: "pl/*.gz"
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- config_name: pt
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data_files: "pt/*.gz"
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- config_name: ro
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data_files: "ro/*.gz"
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- config_name: ru
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data_files: "ru/*.gz"
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- config_name: sk
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data_files: "sk/*.gz"
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- config_name: sl
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data_files: "sl/*.gz"
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- config_name: sv
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data_files: "sv/*.gz"
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- config_name: sw
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data_files: "sw/*.gz"
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- config_name: th
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data_files: "th/*.gz"
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- config_name: tr
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data_files: "tr/*.gz"
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language:
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- bg
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- br
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- ca
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- cs
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- da
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- de
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- el
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- en
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- eo
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- es
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- et
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- eu
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- fa
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- fi
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- fr
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- gl
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- he
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- hr
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- hu
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- hy
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- id
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- it
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- ko
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- "no"
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- pl
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- pt
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- ro
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- ru
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- sk
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- sl
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- sv
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- sw
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- th
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- tr
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size_categories:
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- n<1K
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- 1K<n<10K
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- 10K<n<100K
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- 100K<n<1M
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task_categories:
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- text-generation
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- fill-mask
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task_ids:
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- language-modeling
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- masked-language-modeling
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tags:
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- academia
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- research
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annotations_creators:
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- no-annotation
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multilinguality:
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- multilingual
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source_datasets:
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- HALvest-R
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---
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<div align="center">
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<h1> HALvest </h1>
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<h3> Open Scientific Papers Harvested from HAL </h3>
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</div>
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---
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## Dataset Description
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- **Repository:** [GitHub](https://github.com/Madjakul/HALvesting/tree/main)
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## Dataset Summary
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### overview:
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This dataset is comprised of fulltext from open papers found on [Hyper Articles en Ligne (HAL)](https://hal.science/). Our dump is mostly english/french but gather papers written in 34 languages across 13 domains.
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You can download the dataset using Hugging Face datasets:
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```py
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from datasets import load_dataset
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ds = load_dataset("Madjakul/HALvest", "en")
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```
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### Details
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Building the dataset is a four steps process: data fetching from HAL, data merging, data enriching and data filtering.
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1. We first request [HAL's API](https://api.archives-ouvertes.fr/docs) in order to gather open research papers and parse it -- effectively sorting papers by language. Then, we download the PDFs of the fetched data.
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2. Using [GROBID](https://github.com/kermitt2/grobid), we convert each PDF to an `xml-tei` format in order to have structured data. We convert each `xml-tei` file to a `txt` format before concatenating it with the paper's.
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3. We compute some statistics about each document.
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4. We filter the data based of off simple ratios to expurge badly encoded documents.
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### Languages
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ISO-639|Language|# Documents|# mT5 Tokens
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-------|--------|-----------|--------
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en|English|442,892|7,606,895,258
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fr|French|193,437|8,728,722,255
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es|Spanish|2,930|68,076,878
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it|Italian|1,172|48,747,986
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pt|Portuguese|934|32,918,832
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+
de|German|646|11,699,417
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+
ru|Russian|245|5,763,532
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+
eu|Basque|112|2,297,460
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+
pl|Polish|43|987,878
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el|Greek|42|1,680,696
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+
ro|Romanian|39|1,298,901
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+
ca|Catalan|28|975,078
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+
da|Danish|26|961,895
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+
br|Breton|24|998,088
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+
ko|Korean|17|226,268
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+
tr|Turkish|17|149,718
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hu|Hungarian|14|577,568
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eo|Esperanto|14|105,286
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fa|Persian|10|190,929
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hy|Armenian|10|127,988
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cs|Czech|9|712,263
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bg|Bulgarian|8|180,146
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id|Indonesian|9|53,075
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he|Hebrew|8|61,283
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hr|Croatian|8|40,621
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et|Estonian|7|20,405
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sv|Swedish|6|270,642
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no|Norwegian|6|62,767
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fi|Finnish|3|17,583
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sw|Swahili|2|73,921
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gl|Galician|2|29,688
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+
th|Thai|1|70,909
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sl|Slovenian|1|22,844
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sk|Slovak|1|12,997
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### Domains
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Domain|Code|# Documents|# mT5 Tokens
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------|----|-----------|------------
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Humanities and Social Sciences|shs|152,818|5,487,738,344
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Computer Science|info|143,229|2,436,890,715
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Life Sciences|sdv|111,038|3,008,633,879
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Engineering Sciences|spi|99,393|2,155,602,249
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Physics|phys|63,557|1,435,905,328
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Mathematics|math|54,393|1,359,277,656
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Chemical Science|chim|38,500|857,617,219
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Environmental Science|sde|30,827|566,560,266
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Sciences of the Universe|sdu|22,917|654,909,131
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Statistics|stat|20,571|1,449,842,318
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229 |
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Cognitive science|scco|11,584|222,832,732
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Quantitative Finance|qfin|3,290|64,970,285
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Nonlinear Sciences|nlin|1,908|29,296,684
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You can browse through every domains and sub-domains here: https://hal.science/browse/domain.
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## Considerations for Using the Data
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The corpus is extracted from the [HAL's open archive](https://hal.science/) which distributes scientific publications following open access principles. The corpus is made up of both creative commons licensed and copyrighted documents (distribution authorized on HAL by the publisher). This must be considered prior to using this dataset for any purpose, other than training deep learning models, data mining etc. We do not own any of the text from which these data has been extracted.
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## Citation
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```bib
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@software{almanach_halvest_2024,
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author = {Kulumba, Francis and Antoun, Wissam and Vimont, Guillaume and Romary, Laurent},
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title = {HALvest: Open Scientific Papers Harvested from HAL.},
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month = April,
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248 |
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year = 2024,
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company = Almanach,
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url = {https://github.com/Madjakul/HALvesting}
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}
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```
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## Dataset Copyright
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|
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The licence terms for HALvest strictly follows the one from HAL. Please refer to the below license when using this dataset.
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- [HAL license](https://doc.archives-ouvertes.fr/en/legal-aspects/)
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4bcdbcd33bae039db58a218db2955c447b9bffdb69e045dc4cf1b41928eccf61 en1.0-0.jsonl.gz
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696b8941a5f9ffa0b356c8ba326ad8d29d1274bf7d8fb5e8f4551d92ccbdb431 en1.0-1.jsonl.gz
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3126c648767e202a2a388b998056346ed9878f1ff76a29398772ac3437c202e8 en1.0-2.jsonl.gz
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d169ea3cf308a7e74a41eca3a8083a411e95ba8af357c0e1d8889db638d08f39 en1.0-3.jsonl.gz
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