Improving zero-shot learning baselines with commonsense knowledge
Zero-shot learning — the problem of training and testing on a completely disjoint set of classes — relies greatly on its ability to transfer knowledge from train classes to test classes. Traditionally semantic embeddings consisting of human-defined attributes or distributed word embeddings are used...
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Main Authors: | , , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/170538 |
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Institution: | Nanyang Technological University |
Language: | English |
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