Semantics and deep learning:
This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compositionality; extralinguistic grounding. Representation of these phenomena in recent neural models...
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| Main Authors: | , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2024
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| Subjects: | |
| Online Access: | DE-12 DE-473 Volltext |
| Summary: | This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compositionality; extralinguistic grounding. Representation of these phenomena in recent neural models is discussed, along with the quality of these representations and ways to evaluate them (datasets, tests, measures). The Element closes with suggestions on possible deeper interactions between theoretical semantics and language technology based on deep learning models |
| Item Description: | Title from publisher's bibliographic system (viewed on 18 Dec 2024) |
| Physical Description: | 1 Online-Ressource (82 Seiten) |
| ISBN: | 9781009542340 |
| DOI: | 10.1017/9781009542340 |
Staff View
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| id | DE-604.BV050175365 |
| illustrated | Not Illustrated |
| indexdate | 2025-04-07T10:01:07Z |
| institution | BVB |
| isbn | 9781009542340 |
| language | English |
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| physical | 1 Online-Ressource (82 Seiten) |
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| publishDate | 2024 |
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| publisher | Cambridge University Press |
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| spelling | Abzianidze, Lasha Verfasser aut Semantics and deep learning Lasha Abzianidze, Lisa Bylinina, Denis Paperno Cambridge Cambridge University Press 2024 1 Online-Ressource (82 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 18 Dec 2024) This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compositionality; extralinguistic grounding. Representation of these phenomena in recent neural models is discussed, along with the quality of these representations and ways to evaluate them (datasets, tests, measures). The Element closes with suggestions on possible deeper interactions between theoretical semantics and language technology based on deep learning models Semantics / Data processing Deep learning (Machine learning) Bylinina, Lisa Verfasser aut Paperno, Denis Verfasser (DE-588)116104874X aut Erscheint auch als Druck-Ausgabe 9781009542395 Erscheint auch als Druck-Ausgabe 9781009542364 https://doi.org/10.1017/9781009542340?locatt=mode:legacy Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Abzianidze, Lasha Bylinina, Lisa Paperno, Denis Semantics and deep learning Semantics / Data processing Deep learning (Machine learning) |
| title | Semantics and deep learning |
| title_auth | Semantics and deep learning |
| title_exact_search | Semantics and deep learning |
| title_full | Semantics and deep learning Lasha Abzianidze, Lisa Bylinina, Denis Paperno |
| title_fullStr | Semantics and deep learning Lasha Abzianidze, Lisa Bylinina, Denis Paperno |
| title_full_unstemmed | Semantics and deep learning Lasha Abzianidze, Lisa Bylinina, Denis Paperno |
| title_short | Semantics and deep learning |
| title_sort | semantics and deep learning |
| topic | Semantics / Data processing Deep learning (Machine learning) |
| topic_facet | Semantics / Data processing Deep learning (Machine learning) |
| url | https://doi.org/10.1017/9781009542340?locatt=mode:legacy |
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