A Call for Standardization and Validation of Text Style Transfer Evaluation
원문 초록
Text Style Transfer (TST) evaluation is, in practice, inconsistent. Therefore, we conduct a meta-analysis on human and automated TST evaluation and experimentation that thoroughly examines existing literature in the field. The meta-analysis reveals a substantial standardization gap in human and automated evaluation. In addition, we also find a validation gap: only few automated metrics have been validated using human experiments. To this end, we thoroughly scrutinize both the standardization and validation gap and reveal the resulting pitfalls. This work also paves the way to close the standardization and validation gap in TST evaluation by calling out requirements to be met by future research.
함께 살펴볼 논문
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Multilingual and Explainable Text Detoxification with Parallel Corpora
Style-Specific Neurons for Steering LLMs in Text Style Transfer
WAS: Dataset and Methods for Artistic Text Segmentation
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings
Style Transfer with Multi-iteration Preference Optimization
토론
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