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iBLEU [1] is an important metric for evaluation of paraphrase generation (for ex [2]). iBLEU measures similarity with reference while penalizing similarity with the input sentence. It will be great if this metric is supported.
Sun, H., & Zhou, M. (2012, July). Joint learning of a dual SMT system for paraphrase generation. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 38-42).
Hosking, T., & Lapata, M. (2021, August). Factorising Meaning and Form for Intent-Preserving Paraphrasing. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) (pp. 1405-1418).
The text was updated successfully, but these errors were encountered:
iBLEU [1] is an important metric for evaluation of paraphrase generation (for ex [2]). iBLEU measures similarity with reference while penalizing similarity with the input sentence. It will be great if this metric is supported.
The text was updated successfully, but these errors were encountered: