Synthetic Reference Dataset

A Synthetic Reference Dataset is a reference dataset that contains artificially generated references created through automated methods or rule-based systems for evaluation benchmarking.

• AKA: Artificial Reference Dataset, Generated Reference Dataset, Automated Reference Collection, Synthetic Benchmark Dataset.
• Context:
  • It can typically enable Large-Scale Generation overcoming annotation bottlenecks.
  • It can typically provide Controlled Variation for systematic testing.
  • It can often reduce Dataset Creation Costs compared to human annotation.
  • It can often support Edge Case Testing through targeted generation.
  • It can facilitate Privacy Preservation avoiding real data exposure.
  • It can enable Multilingual Coverage through translation systems.
  • It can incorporate Quality Filters ensuring reference validity.
  • It can integrate with Data Augmentation expanding training sets.
  • It can range from being a Template-Based Synthetic Dataset to being a Model-Generated Synthetic Dataset, depending on its generation method.
  • It can range from being a High-Fidelity Synthetic Dataset to being a Low-Fidelity Synthetic Dataset, depending on its realism level.
  • It can range from being a Domain-Specific Synthetic Dataset to being a General Synthetic Dataset, depending on its content scope.
  • It can range from being a Static Synthetic Dataset to being a Dynamic Synthetic Dataset, depending on its generation timing.
  • ...
• Examples:
  • Generation Methods, such as:
    • Template-Based Reference Dataset using pattern instantiation.
    • Paraphrase-Based Reference Dataset using semantic variation.
    • Back-Translation Reference Dataset using round-trip translation.
  • Task-Specific Synthetic Datasets, such as:
    • Synthetic QA Dataset for question answering.
    • Synthetic Dialogue Dataset for conversation systems.
    • Synthetic Summary Dataset for summarization tasks.
  • Augmentation Datasets, such as:
    • Adversarial Reference Dataset for robustness testing.
    • Perturbation-Based Dataset for stability evaluation.
  • ...
• Counter-Examples:
  • NLG Gold Reference Dataset, which uses human curation.
  • Crowd-Sourced Dataset, which uses human annotation.
  • Natural Corpus, which contains authentic text.
• See: Reference Dataset, NLG Gold Reference Dataset, Evaluation Reference Dataset, Data Generation Method, Synthetic Data, Automated Annotation, Data Augmentation.

---