Reference-guided and reference-free strategies are methods used to construct diverse and realistic datasets or benchmarks, particularly for tasks involving complex instructions or content generation. They ensure a broad spectrum of scenarios, from mimicking existing examples to creating novel ones.
These strategies are ways to create test cases or datasets for AI models. 'Reference-guided' means making new examples similar to existing ones, ensuring they are realistic. 'Reference-free' means creating completely new and diverse examples, often to test unusual situations.
data generation strategies, instruction generation methods, synthetic data generation, benchmark construction methods
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