Summary of On the Self-verification Limitations Of Large Language Models on Reasoning and Planning Tasks, by Kaya Stechly et al.
On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks
by Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati
First submitted to arxiv on: 12 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 research paper investigates the reasoning abilities of Large Language Models (LLMs) by analyzing their performance in three domains: Game of 24, Graph Coloring, and STRIPS planning. The authors examine whether LLMs can self-critique and improve their own solutions through iterative prompting, as well as the effectiveness of external verification in enhancing performance. They experiment with GPT-4, a state-of-the-art language model, and find that while self-critique leads to significant performance collapse, external verification yields substantial gains. The study also shows that simply re-prompting with a sound verifier maintains most of the benefits. The results challenge prevailing assumptions about LLMs’ reasoning capabilities and have implications for their potential applications. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research paper looks at how well Large Language Models (LLMs) can think for themselves. It tries to figure out if these models can improve their answers by giving them feedback on why those answers are correct or not. The scientists tested a really smart language model called GPT-4 and found that when it tried to give itself feedback, it actually got worse! But when they gave it feedback from someone else, it did much better. This is important because it means we might be able to make these models even more useful by helping them learn from their mistakes. |
Keywords
» Artificial intelligence » Gpt » Language model » Prompting
