Papers by Shaul Markovitch
Interpreting Embedding Spaces by Conceptualization (2023.emnlp-main)
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| Challenge: | Recent advances in large language models have a significant drawback: they are incomprehensible to humans. |
| Approach: | They propose a method for understanding embeddings by transforming a latent embeddable space into a comprehensible conceptual space. |
| Outcome: | The proposed method compares the semantics of the original latent embedding space to the semantic of the vectors. |
A Two-Stage Masked LM Method for Term Set Expansion (2020.acl-main)
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| Challenge: | Existing methods for Term Set Expansion are either distributional or pattern-based . Term set expansion is a task of expanding a small seed set of example terms into a larger set of terms that belong to the same semantic category. |
| Approach: | They propose a method which uses neural masked language models to expand a small seed set of terms into a larger set of semantic terms. |
| Outcome: | The proposed method outperforms state-of-the-art methods due to the small seed set size . it uses neural masked language models to query large, pre-trained mlms . |