| Challenge: | a snowclone is a customizable phrasal template that can be realized in multiple, instantly recognized variants. |
| Approach: | They propose to use pop-culture quotes to train algorithms to detect cultural references in text. |
| Outcome: | The proposed algorithm can detect cultural references in pop-culture quotes and train on them. |
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| Challenge: | Using a novel task, we advocate automatic pull quote selection to engage readers with thought-provoking articles . pull quotes increase enjoyment and readability, shape reader perceptions, and facilitate learning. |
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| Challenge: | Dog whistles are coded expressions with dual meanings that slip by content moderation filters . a new study finds that state-of-the-art systems fail to identify novel dog whistles . |
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| Challenge: | Quotation extraction is a useful task, but it is not widely studied in other languages. |
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Unsupervised Neologism Normalization Using Embedding Space Mapping (D19-55)
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| Challenge: | Large language models (LLMs) can be used to enhance text quality but can sometimes result in loss or distortion of original meaning. |
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MUDES: Multilingual Detection of Offensive Spans (2021.naacl-demos)
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| Challenge: | Identifying offensive spans in texts is the goal of the SemEval-2021 Task 5: Toxic Spans Detection . previous work focused on post level annotations, but identifying offensive span is useful in many ways. |
| Approach: | They propose a Python-based system to detect offensive spans in texts with pre-trained models and a user-friendly web-based interface. |
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