Papers by Mayank Kumar Nagda

2 papers
A Call for Standardization and Validation of Text Style Transfer Evaluation (2023.findings-acl)

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Challenge: Text style transfer (TST) evaluation is inconsistent in practice.
Approach: They conduct a meta-analysis on human and automated TST evaluation and experimentation . they find a standardization gap and a validation gap in the field .
Outcome: The authors find that evaluation procedures are inconsistent and that they need to improve on them.
Text Style Transfer Evaluation Using Large Language Models (2024.lrec-main)

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Challenge: Recent advances in large language models (LLMs) have demonstrated their capacity to match and even exceed average human performance across diverse, unseen tasks.
Approach: They compare the results of different LLMs in TST evaluation using multiple input prompts and introduce the concept of prompt ensembling.
Outcome: The proposed model outperforms human evaluations on multiple input prompts.

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