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title: "Who cites A Statistical Analysis of — 69 citing papers"
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# Who cites «A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods»

69 papers of our library cite it (of the 141,840 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods»](https://md.research.elamur.ai/free/en/papers/deutsch-2021-statistical-analysis-summarization-evaluation-metrics/)

1. [**Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation arXiv:2212.07981**Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.*2022 · 116 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-revisiting-gold-standard-grounding-summarization/) **[LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization](https://md.research.elamur.ai/free/en/papers/krishna-2023-longeval-guidelines-human-evaluation-faithfulness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kalpesh Krishna, Erin Bransom, Bailey Kuehl, et al.*2023 · 113 citations* **[LENS: A Learnable Evaluation Metric for Text Simplification](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations* **[Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://md.research.elamur.ai/free/en/papers/vernikos-2022-embarrassingly-easy-document-level-mt/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Giorgos Vernikos, Brian Thompson, Prashant Mathur, et al.*2022 · 68 citations* **[Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!](https://md.research.elamur.ai/free/en/papers/perrella-2024-guardians-machine-translation-meta-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Stefano Perrella, Lorenzo Proietti, Alessandro Scirè, et al.*2024 · 24 citations* **[Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations](https://md.research.elamur.ai/free/en/papers/tan-2026-remedy-r-generative-reasoning-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary, et al.*2026 · 2 citations* **[PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation](https://md.research.elamur.ai/free/en/papers/proietti-2026-pear-pairwise-evaluation-automatic-relative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Proietti, Roman Grundkiewicz, Matt Post*2026 · 1 citation*

57 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/deutsch-2021-statistical-analysis-summarization-evaluation-metrics/) — A Statistical Analysis of Summarization Evaluation Metrics Using Resampling Methods