Summary of Large Language Models As a Tool For Mining Object Knowledge, by Hannah Youngeun An and Lenhart K. Schubert
Large Language Models as a Tool for Mining Object Knowledge
by Hannah YoungEun An, Lenhart K. Schubert
First submitted to arxiv on: 16 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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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 commonsense knowledge of large language models (LLMs) regarding everyday physical objects, focusing on their parts and materials. The authors hypothesize that LLMs’ general knowledge about these objects is largely sound, but tend to confabulate facts when questioned about obscure entities or technical domains. To test this hypothesis, the researchers use few-shot with five in-context examples and zero-shot multi-step prompting to generate a repository of data on the parts and materials of around 2,300 objects and their subtypes. The evaluation demonstrates LLMs’ coverage and soundness in extracting knowledge. This contribution to knowledge mining can be useful for AI research on reasoning about object structure and composition. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how well large language models (LLMs) know about everyday things, like objects we use every day. The researchers want to see if LLMs are good at telling us what these objects are made of and what their parts are. They think that LLMs are generally pretty good at this, but might not be so sure when asked about complicated or technical things. To test this idea, the researchers gave the models some examples and asked them to come up with a list of all the different objects they know something about. When they checked how well the models did, they found that LLMs are actually pretty good at giving accurate information. |
Keywords
» Artificial intelligence » Few shot » Prompting » Zero shot
