Papers by Diwakar Mahajan

1 papers
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types (2023.findings-acl)

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Challenge: Existing evaluation metrics for machine text are inadequate to capture quality of text . a recent study has focused on task-specific evaluation metrics or on properties of machine-generated text based on mismatch errors .
Approach: They propose a new evaluation scheme based on fine-grained mismatch errors . they propose 13 mismatch error types to guide the model for better prediction of human judgments .
Outcome: The proposed evaluation scheme is based on mismatch errors in 7 NLP tasks . the mismatch error types guide the model for better prediction of human judgments .

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