Summary of Autoregressive + Chain Of Thought = Recurrent: Recurrence’s Role in Language Models’ Computability and a Revisit Of Recurrent Transformer, by Xiang Zhang et al.
Autoregressive + Chain of Thought = Recurrent: Recurrence’s Role in Language Models’ Computability and a Revisit of Recurrent Transformer
by Xiang Zhang, Muhammad Abdul-Mageed, Laks V.S. Lakshmanan
First submitted to arxiv on: 14 Sep 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 This paper investigates the role of recurrent structures in neural language models, particularly Transformer-based models. Despite their success in various tasks, Transformers have limitations due to their lack of recurrent connections. This restricts their computational abilities, making them struggle with simple tasks like counting and multiplication. The authors propose the “Chain of Thought” (CoT) prompting approach as a bridge between autoregression and recurrence, allowing Transformers to tackle previously impossible tasks. They also examine recent recurrent-based Transformer designs, introducing the concept of “recurrence-completeness.” This work aims to provide insights into neural model architectures and prompt better design. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how language models, like those used in chatbots, are limited by their design. Transformers, which do well with language tasks, have trouble with simple math problems because they don’t use a special type of connection called recurrent connections. The authors explore an idea called “Chain of Thought” that helps these models do better on tricky tasks. They also compare different designs for Transformers and introduce a new concept to help people design better models. |
Keywords
» Artificial intelligence » Prompt » Prompting » Transformer
