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Related Questions
- What are the limitations of current LLMs in understanding context and common sense, and how can they be addressed?
- How do memory-augmented neural networks (MANNs) improve context switching in LLMs?
- What is the role of attention mechanisms in facilitating context switching and common sense reasoning in LLMs?
- Can you explain the concept of 'contextual' understanding in LLMs and how it differs from traditional 'task-oriented' understanding?
- How do LLMs leverage external knowledge sources, such as knowledge graphs, to improve common sense reasoning and context switching?
- What are the key differences between 'long-range' and 'short-range' contextual dependencies in LLMs, and how do they impact common sense reasoning?
- Can you discuss the trade-offs between increasing the complexity of LLMs to improve context switching and common sense reasoning, versus keeping the models simple and efficient for deployment?
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