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Related Questions
- Can a language model that lacks common sense or real-world experience accurately identify analogies between concepts?
- How does the absence of real-world experience affect a language model's ability to recognize patterns and relationships in analogical reasoning?
- In what ways can a language model's lack of common sense impact its ability to generate coherent and relevant analogies?
- Can a language model with limited real-world experience learn to recognize analogies through extensive training data, or is it inherently limited?
- How does the lack of common sense or real-world experience impact the language model's ability to understand context and nuances in analogical reasoning?
- Can a language model's analogical reasoning abilities be improved by incorporating real-world data or common sense knowledge, and if so, how?
- What are the limitations of analogical reasoning in language models that lack common sense or real-world experience, and how can these limitations be addressed?
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