Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing (2021.eacl-demos)
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| Challenge: | Trankit is a lightweight, pre-trained toolkit for multilingual natural language processing. |
| Approach: | They propose a transformer-based toolkit for multilingual natural language processing that trains pipelines over 100 languages and 90 pretrained pipelines for 56 languages. |
| Outcome: | The proposed tool outperforms existing pipelines over sentence segmentation, part-of-speech tagging, morphological feature tabbing, and dependency parsing while maintaining competitive performance over tokenization, multi-word token expansion, and lemmatization over 90 Universal Dependencies treebanks. |
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Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vulić, Sebastian Ruder, Kyunghyun Cho, Iryna Gurevych
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Robust Transfer Learning with Pretrained Language Models through Adapters (2021.acl-short)
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| Challenge: | Existing approaches to transfer learning with pretrained transformer-based language models are not robust and can be adversarial. |
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