| Challenge: | Scientific research continually discovers and invents new concepts, which are then referred to by new terms, neologisms, or nenonyms. |
| Approach: | They propose to leverage term definitions to translate neologisms with Large Language Models . they find that LLMs generate terms from co-hyponyms and terms sharing the same derivation paradigm . |
| Outcome: | The proposed model can generate terms from co-hyponyms and terms sharing the same derivation paradigm. |
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| Challenge: | etymology is the study of words' origins. |
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| Challenge: | Unfamiliar terminology and complex language can make understanding science difficult for readers. |
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A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (2024.emnlp-main)
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Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora (2020.findings-emnlp)
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| Challenge: | Existing research on knowledge transfer focuses on documents as unit of analysis and follow their transfer into practice for a specific scientific domain. |
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Phrase-Based & Neural Unsupervised Machine Translation (D18-1)
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Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing (D19-60)
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