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Link paper in dataset card

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  # Dataset Card for SMESum
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  ## Dataset Summary
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- SMESum is a deterministic reproduction of the Slovak news summarization corpus introduced by Šuppa and Adamec (2020). It contains Slovak news articles sourced from the SME news portal via the Internet Archive. Each example provides the full article (`document`) together with two short abstractive fields (`title`, `introduction`) that can be concatenated to form the gold summary, mirroring the setup described in the paper. The corpus is split into train/validation/test partitions of sizes 64,001/8,001/8,001 using a salted SHA-256 hash of each filename to guarantee reproducibility.
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  ## Supported Tasks and Leaderboards
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- - `summarization`: Abstractive or extractive summarization of Slovak news articles. The original paper benchmarks multiple extractive baselines, including TextRank and a multilingual BERT model fine-tuned for extractive summarization.
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  - `classification`: The classification of content into categories / SME section labels (e.g. `sport`).
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  ## Languages
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  | validation | 8,001 | 344.99 | 18.18 | 23.58 | 2.16 |
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  | test | 8,001 | 332.25 | 17.96 | 23.46 | 2.15 |
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- Statistics replicate Table 2 in Šuppa and Adamec (2020).
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  ### Loading with `datasets`
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  ## Data Collection
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  - **Source**: SME.sk, a major Slovak news portal. Articles were harvested from archived snapshots hosted by the Internet Archive.
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- - **Timeframe**: Articles span multiple years leading up to late 2019, in line with the crawl described in the paper.
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  - **Selection criteria**: Paid-content stubs and incomplete articles were excluded. Categories cover general news, world affairs, business, sports, travel, tech, culture, and opinion.
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  ## Citation
 
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  # Dataset Card for SMESum
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  ## Dataset Summary
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+ SMESum is a deterministic reproduction of the Slovak news summarization corpus introduced by [Šuppa and Adamec (2020)](https://aclanthology.org/2020.lrec-1.830/). It contains Slovak news articles sourced from the SME news portal via the Internet Archive. Each example provides the full article (`document`) together with two short abstractive fields (`title`, `introduction`) that can be concatenated to form the gold summary, mirroring the setup described in the paper. The corpus is split into train/validation/test partitions of sizes 64,001/8,001/8,001 using a salted SHA-256 hash of each filename to guarantee reproducibility.
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  ## Supported Tasks and Leaderboards
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+ - `summarization`: Abstractive or extractive summarization of Slovak news articles. The [original paper](https://aclanthology.org/2020.lrec-1.830/) benchmarks multiple extractive baselines, including TextRank and a multilingual BERT model fine-tuned for extractive summarization.
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  - `classification`: The classification of content into categories / SME section labels (e.g. `sport`).
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  ## Languages
 
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  | validation | 8,001 | 344.99 | 18.18 | 23.58 | 2.16 |
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  | test | 8,001 | 332.25 | 17.96 | 23.46 | 2.15 |
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+ Statistics replicate Table 2 in [Šuppa and Adamec (2020)](https://aclanthology.org/2020.lrec-1.830/).
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  ### Loading with `datasets`
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  ## Data Collection
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  - **Source**: SME.sk, a major Slovak news portal. Articles were harvested from archived snapshots hosted by the Internet Archive.
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+ - **Timeframe**: Articles span multiple years leading up to late 2019, in line with the crawl described in [Šuppa and Adamec (2020)](https://aclanthology.org/2020.lrec-1.830/).
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  - **Selection criteria**: Paid-content stubs and incomplete articles were excluded. Categories cover general news, world affairs, business, sports, travel, tech, culture, and opinion.
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  ## Citation