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Related Questions
- How can we leverage human evaluation to ensure that negative examples are contextually relevant?
- What are some strategies for designing contextual scenarios that elicit negative examples?
- Can we use natural language processing techniques to identify and generate contextually appropriate negative examples?
- How can we use active learning to select the most informative negative examples for contextual understanding?
- What role can crowdsourcing play in collecting high-quality negative examples that account for contextual understanding?
- Can we develop a framework for evaluating the contextual relevance of negative examples?
- How can we use transfer learning to adapt negative example collection to different domains and contexts?
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