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license: mit
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---
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@@ -44,4 +54,27 @@ The paper is available [here](https://aclanthology.org/2025.swisstext-1.9/).
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| **Training Data** | PubTabNet + SynthTabNet (all subsets) |
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| **Metrics** | S-TEDS: 99.36 on SynthTabNet and 97.36 on PubTabNet |
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---
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license: mit
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datasets:
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- dimtri009/SLANet-1M_dataset
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language:
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- en
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base_model:
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- PaddlePaddle/SLANet
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tags:
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- table-recognition
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- table-structure-recognition
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- slanet-1m
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---
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| **Training Data** | PubTabNet + SynthTabNet (all subsets) |
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| **Metrics** | S-TEDS: 99.36 on SynthTabNet and 97.36 on PubTabNet |
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---
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Please cite us:
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```
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@inproceedings{romaric-etal-2025-slanet,
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title = "{SLAN}et-1{M}: A Lightweight and Efficient Model for Table Recognition with Minimal Computational Cost",
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author = "Romaric, Nguinwa Mbakop Dimitri and
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Petrucci, Andrea and
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Marinai, Simone and
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Hennebert, Jean",
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editor = {Gerber, Jonathan and
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Cieliebak, Mark and
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Tuggener, Don and
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H{\"u}rlimann, Manuela},
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booktitle = "Proceedings of the 10th edition of the Swiss Text Analytics Conference",
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month = may,
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year = "2025",
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address = "Winterthur, Switzerland",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2025.swisstext-1.9/",
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pages = "89--102"
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}
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```
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