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Related Questions
- How do large language models handle unclear language in user input?
- What contextual analysis techniques do large language models employ to resolve ambiguity?
- What strategies do large language models use to disambiguate homographs and polysemy?
- How do large language models incorporate world knowledge and general knowledge to resolve contextual ambiguity?
- Can you explain the concept of 'coreference' and its role in resolving contextual ambiguity in large language models?
- How do large language models address the problem of multiple intents in a single sentence or conversation?
- What is the concept of 'entity disambiguation' and how is it used in large language models to resolve ambiguity?
- What machine learning techniques are used by large language models to adapt to changing contexts and update their understanding of context-dependent information?
- How do large language models handle implicit information in conversations, such as presupposition and inference?
- What role do semantics and pragmatics play in resolving contextual ambiguity in large language models?
- Can you provide examples of how large language models use contextual cues like tone, syntax, and discourse structure to infer speaker intent and resolve ambiguity?
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