LLMs4Implicit-knowledge-generation public
Code for equipping pretrained language models (BART, GPT-2, XLNet) with commonsense knowledge for generating implicit knowledge statements between two sentences, by (i) finetuning the models on corpora enriched with implicit information; and by (ii) constraining models with key concepts and commonse...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Dokumenttyp: | Datenbank Forschungsdaten |
| Sprache: | Englisch |
| Veröffentlicht: |
Heidelberg
Universität
2024-02-26
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| DOI: | 10.11588/data/5VTJ26 |
| Schlagworte: | |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.11588/data/5VTJ26 Verlag, kostenfrei, Volltext: https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/DATA/5VTJ26 
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| Verfasserangaben: | Maria Becker |
MARC
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| 520 | |a Code for equipping pretrained language models (BART, GPT-2, XLNet) with commonsense knowledge for generating implicit knowledge statements between two sentences, by (i) finetuning the models on corpora enriched with implicit information; and by (ii) constraining models with key concepts and commonsense knowledge paths connecting them. | ||
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