| Challenge: | a recent study shows that deep learning models can be used to solve textual inference tasks using simple linguistic patterns. |
| Approach: | They propose a set of syntactic tasks focused on contradiction detection that exploit linguistic patterns. |
| Outcome: | The proposed tasks can be implemented in English and Portuguese. |
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| Challenge: | Recent research on textual entailment is limited to English, but it is expanding to other languages. |
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Logical Transformers: Infusing Logical Structures into Pre-Trained Language Models (2023.findings-acl)
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Borui Wang, Qiuyuan Huang, Budhaditya Deb, Aaron Halfaker, Liqun Shao, Daniel McDuff, Ahmed Hassan Awadallah, Dragomir Radev, Jianfeng Gao
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| Challenge: | Natural Language Inference (NLI) is a crucial task in AI and natural language processing. |
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| Challenge: | Multilingual Transformer-based language models have been shown to be excellent learners in crosslingual transfer tasks. |
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Emerging Cross-lingual Structure in Pretrained Language Models (2020.acl-main)
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| Challenge: | Recent work has shown that multilingual pretraining works, but is unable to measure these effects. |
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XNLI: Evaluating Cross-lingual Sentence Representations (D18-1)
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Combining Deep Generative Models and Multi-lingual Pretraining for Semi-supervised Document Classification (2021.eacl-main)
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Model-Agnostic Cross-Lingual Training for Discourse Representation Structure Parsing (2024.lrec-main)
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A Checkpoint on Multilingual Misogyny Identification (2022.acl-srw)
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| Challenge: | a study on hate speech against minorities in Italian tweets found that 1 women are the most targeted group. |
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