Summary of Transformers, Contextualism, and Polysemy, by Jumbly Grindrod
Transformers, Contextualism, and Polysemy
by Jumbly Grindrod
First submitted to arxiv on: 15 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores the transformer architecture’s potential in developing a theory about the relationship between context and meaning. It draws from the way transformers work to argue that this theory, dubbed “transformer theory,” offers novel insights into two long-standing debates: contextualism and polysemy. By examining how the transformer architecture processes language, the author aims to provide a new perspective on these fundamental questions in natural language processing. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how a special kind of computer model called a transformer helps us understand how words mean different things depending on what’s around them. It thinks that this idea can help solve two big problems in understanding human language: figuring out when context matters and dealing with words that have many meanings. By studying how transformers work, the author hopes to provide new answers to these long-standing questions. |
Keywords
» Artificial intelligence » Natural language processing » Transformer
