Scalable syntactic inductive biases for neural language models
<p>Natural language has a sequential surface form, although its underlying structure has been argued to be hierarchical and tree-structured in nature, whereby smaller linguistic units like words are recursively composed to form larger ones, such as phrases and sentences. This thesis aims to an...
Päätekijä: | Kuncoro, AS |
---|---|
Muut tekijät: | Blunsom, P |
Aineistotyyppi: | Opinnäyte |
Kieli: | English |
Julkaistu: |
2022
|
Aiheet: |
Samankaltaisia teoksia
-
Incremental generative models for syntactic and semantic natural language processing
Tekijä: Buys, J
Julkaistu: (2017) -
Large Language Models are Not Models of Natural Language: They are Corpus Models
Tekijä: Csaba Veres
Julkaistu: (2022-01-01) -
Understanding video through the lens of language
Tekijä: Bain, M
Julkaistu: (2023) -
Simplicity and learning to distinguish arguments from modifiers
Tekijä: Leon Bergen, et al.
Julkaistu: (2022-12-01) -
Non-parametric deep learning with applications in active learning
Tekijä: Band, N
Julkaistu: (2022)