Summary of Can Large Language Models Act As Symbolic Reasoners?, by Rob Sullivan et al.
Can Large Language Models Act as Symbolic Reasoners?
by Rob Sullivan, Nelly Elsayed
First submitted to arxiv on: 28 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Emerging Technologies (cs.ET)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 abstract presents an investigation into the ability of Large Language Models (LLMs) to reason about their processes and conclusions. The authors critique LLMs for not being able to explain their decision-making, highlighting the need for a plan or strategy to approach this problem. The paper reviews current research on symbolic reasoning and LLMs, exploring whether an LLM can inherently provide reasoning capabilities or if supporting components are necessary. It also aims to identify gaps in existing research and suggest future trends in LLM explainability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models (LLMs) have shown impressive performance across many areas, but some people think they can’t really understand what they’re doing or why. This paper looks at how LLMs think about their own thinking and decisions. It also tries to figure out if an LLM is smart enough to come up with its own ideas or if it needs help from other parts. If the LLM is smart, does this mean it can do it in any area or just some specific ones? |
