Summary of Can Large Language Models Reason and Plan?, by Subbarao Kambhampati
Can Large Language Models Reason and Plan?
by Subbarao Kambhampati
First submitted to arxiv on: 7 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG)
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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 whether large language models (LLMs) can correct their own errors through self-critiquing. Unlike humans, who occasionally recognize and rectify their own mistaken assumptions, LLMs do not appear to possess this capability. The study reveals that LLMs lack the ability to engage in self-correction, contradicting the assumption that they might exhibit this human-like trait. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are artificial intelligence systems that can make mistakes just like humans do. This paper looks at whether these models can correct their own errors by thinking critically about them. The answer is no – LLMs don’t have the ability to recognize and fix their own mistakes, unlike people who sometimes realize they’re wrong and change their minds. |
