Who cites «Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts»
- MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence FrontiersarXiv:2102.01454Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, et al.2021 · 244 citationsTowards a Unified Multi-Dimensional Evaluator for Text GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Ming Zhong, Yang Liu, Da Yin, et al.2022 · 205 citations
- Binding Language Models in Symbolic LanguagesarXiv:2210.02875Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.2022 · 167 citationsGO FIGURE: A Meta Evaluation of Factuality in SummarizationFindings of the Association for Computational LinguisticsSaadia Gabriel, Asli Celikyilmaz, Rahul Jha, et al.2021 · 129 citationsTomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering EvaluationConference on Empirical Methods in Natural Language Processing (EMNLP)Jannis Bulian, Christian Buck, Wojciech Gajewski, et al.2022 · 100 citationsLearning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared TaskConference on Machine Translation (WMT)Thibault Sellam, Amy Pu, Hyung Won Chung, et al.2020 · 55 citations
Re-evaluating Evaluation in Text SummarizationConference on Empirical Methods in Natural Language Processing (EMNLP)Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, et al.2020 · 258 citations
This page in Markdown → https://md.research.elamur.ai/free/en/papers/clark-2019-sentence-mover-s-similarity-automatic/cited-by/