---
title: "Who cites Miles Osborne"
description: "684 papers of the Elamur Research library cite the works of Miles Osborne, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/miles-osborne/cited-by/"
---
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# Who cites Miles Osborne

702 citations of their works from 684 papers of our library (of the 140,884 whose bibliographies we read) · 40 with a page here, the most cited first · [← Miles Osborne](https://md.research.elamur.ai/free/en/authors/miles-osborne/)

1. [**Active Learning Literature Survey**Burr Settles*2009 · 4,889 citations*](https://md.research.elamur.ai/free/en/papers/settles-2009-active-learning-literature-survey/)
2. [**SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems**Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.*2019 · 2,187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/)
3. [**CIDEr: Consensus-based Image Description Evaluation**Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh*2014 · 733 citations*](https://md.research.elamur.ai/free/en/papers/vedantam-2014-cider-consensus-based-image-description/)
4. [**Red Teaming Language Models with Language Models**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 665 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/)
5. [**A Structured Review of the Validity of BLEU**Ehud Reiter*2018 · 538 citations*](https://md.research.elamur.ai/free/en/papers/reiter-2018-structured-review-validity-bleu/)
6. [**Experiments in Domain Adaptation for Statistical Machine Translation**Philipp Koehn, Josh Schroeder*2007 · 481 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2007-experiments-domain-adaptation-statistical-machine/)
7. [**Automatic Evaluation of Translation Quality for Distant Language Pairs**Hideki Isozaki, Tsutomu Hirao, Kevin Duh, et al.*2010 · 461 citations*](https://md.research.elamur.ai/free/en/papers/isozaki-2010-automatic-evaluation-translation-quality-distant/)
8. [**Manual and Automatic Evaluation of Machine Translation between European Languages**Philipp Koehn, Christof Monz*2006 · 433 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2006-manual-automatic-evaluation-machine-translation/)
9. [**Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics**Nitika Mathur, Timothy Baldwin, Trevor Cohn*2020 · 385 citations*](https://md.research.elamur.ai/free/en/papers/mathur-2020-tangled-up-bleu-reevaluating-evaluation/)
10. [**cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models**Chris Dyer, Adam Lopez, Juri Ganitkevitch, et al.*2010 · 372 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2010-cdec-decoder-alignment-learning-framework/)
11. [**Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation**Deyi Xiong, Qun Liu, Shouxun Lin*2006 · 360 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2006-maximum-entropy-based-phrase-reordering/)
12. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
13. [**Statistical Approaches to Computer-Assisted Translation**Sergio Barrachina, Oliver Bender, Francisco Casacuberta, et al.*2008 · 313 citations*](https://md.research.elamur.ai/free/en/papers/barrachina-2009-statistical-approaches-computer-assisted-translation/)
14. [**Why We Need New Evaluation Metrics for NLG**Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, et al.*2017 · 287 citations*](https://md.research.elamur.ai/free/en/papers/novikova-2017-why-we-need-new-evaluation/)
15. [**A Survey of Paraphrasing and Textual Entailment Methods**Ion Androutsopoulos, Prodromos Malakasiotis*2009 · 280 citations*](https://md.research.elamur.ai/free/en/papers/androutsopoulos-2009-survey-paraphrasing-textual-entailment-methods/)
16. [**How Noisy Social Media Text, How Diffrnt Social Media Sources?**Timothy Baldwin, Paul Cook, Marco Lui, et al.*2013 · 275 citations*](https://md.research.elamur.ai/free/en/papers/baldwin-2013-how-noisy-social-media-text/)
17. [**A Comparison of Pivot Methods for Phrase-Based Statistical Machine Translation**Masao Utiyama, Hitoshi Isahara*2007 · 263 citations*](https://md.research.elamur.ai/free/en/papers/utiyama-2007-comparison-pivot-methods-phrase-based/)
18. [**BLEU is Not Suitable for the Evaluation of Text Simplification**Elior Sulem, Omri Abend, Ari Rappoport*2018 · 255 citations*](https://md.research.elamur.ai/free/en/papers/sulem-2018-bleu-is-not-suitable-evaluation/)
19. [**Generalizing Word Lattice Translation**Christopher Dyer, Smaranda Muresan, Philip Resnik*2008 · 249 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2008-generalizing-word-lattice-translation/)
20. [**SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)**Wei Xu, Chris Callison-Burch, Bill Dolan*2015 · 230 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-semeval-2015-task-1-paraphrase/)
21. [**BLEU might be Guilty but References are not Innocent**Markus Freitag, David Grangier, Isaac Caswell*2020 · 223 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2020-bleu-might-be-guilty-but/)
22. [**(Meta-) Evaluation of Machine Translation**Chris Callison-Burch, Cameron Fordyce, Philipp Koehn, et al.*2007 · 206 citations*](https://md.research.elamur.ai/free/en/papers/burch-2007-meta-evaluation-machine-translation/)
23. [**Jointly Learning to Align and Translate with Transformer Models**Sarthak Garg, Stephan Peitz, Udhyakumar Nallasamy, et al.*2019 · 199 citations*](https://md.research.elamur.ai/free/en/papers/garg-2019-jointly-learning-align-translate-transformer/)
24. [**Analyzing Uncertainty in Neural Machine Translation**Myle Ott, Michael Auli, David Grangier, et al.*2018 · 190 citations*](https://md.research.elamur.ai/free/en/papers/ott-2018-analyzing-uncertainty-neural-machine-translation/)
25. [**Fill-up versus interpolation methods for phrase-based SMT adaptation**Arianna Bisazza, Nick Ruiz, Marcello Federico*2011 · 152 citations*](https://md.research.elamur.ai/free/en/papers/bisazza-2011-fill-up-versus-interpolation-methods/)
26. [**Learning Compact Metrics for MT**Amy Pu, Hyung Won Chung, Ankur Parikh, et al.*2021 · 130 citations*](https://md.research.elamur.ai/free/en/papers/pu-2021-learning-compact-metrics-mt/)
27. [**Fast, Cheap, and Creative: Evaluating Translation Quality Using Amazon's Mechanical Turk**Chris Callison-Burch*2009 · 112 citations*](https://md.research.elamur.ai/free/en/papers/burch-2009-fast-cheap-creative-evaluating-translation/)
28. [**Measuring Machine Translation Errors in New Domains**Ann Irvine, John Morgan, Marine Carpuat, et al.*2013 · 104 citations*](https://md.research.elamur.ai/free/en/papers/irvine-2013-measuring-machine-translation-errors-new/)
29. [**Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus**Luisa Bentivogli, Beatrice Savoldi, Matteo Negri, et al.*2020 · 100 citations*](https://md.research.elamur.ai/free/en/papers/bentivogli-2020-gender-danger-evaluating-speech-translation/)
30. [**Towards broad coverage surface realization with CCG**Michael White, Rajakrishnan Rajkumar, Scott Martin*2007 · 73 citations*](https://md.research.elamur.ai/free/en/papers/white-2007-broad-coverage-surface-realization-ccg/)
31. [**Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation**Thiago Castro Ferreira, Iacer Calixto, Sander Wubben, et al.*2017 · 46 citations*](https://md.research.elamur.ai/free/en/papers/ferreira-2017-linguistic-realisation-as-machine-translation/)
32. [**Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments**Marina Fomicheva, Lucia Specia*2019 · 44 citations*](https://md.research.elamur.ai/free/en/papers/fomicheva-2019-taking-mt-evaluation-metrics-extremes/)
33. [**Discourse Structure in Machine Translation Evaluation**Shafiq Joty, Francisco Guzmán, Lluís Màrquez, et al.*2017 · 40 citations*](https://md.research.elamur.ai/free/en/papers/joty-2017-discourse-structure-machine-translation-evaluation/)
34. [**Feature-Rich Translation by Quasi-Synchronous Lattice Parsing**Kevin Gimpel, Noah A. Smith*2009 · 30 citations*](https://md.research.elamur.ai/free/en/papers/gimpel-2009-feature-rich-translation-quasi-synchronous/)
35. [**Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets**Nikita Moghe, Arnisa Fazla, Chantal Amrhein, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/moghe-2025-machine-translation-meta-evaluation-through/)
36. [**Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?**Ajay Patel, Nicholas Andrews, Chris Callison-Burch*2022 · 24 citations*](https://md.research.elamur.ai/free/en/papers/patel-2022-low-resource-authorship-style-transfer/)
37. [**Anaphora Models and Reordering for Phrase-Based SMT**Christian Hardmeier, Sara Stymne, Jörg Tiedemann, et al.*2014 · 13 citations*](https://md.research.elamur.ai/free/en/papers/hardmeier-2014-anaphora-models-reordering-phrase-based/)
38. [**Towards Heterogeneous Automatic MT Error Analysis**Jesús Giménez, Lluís Màrquez*2008 · 13 citations*](https://md.research.elamur.ai/free/en/papers/gimenez-2008-heterogeneous-automatic-mt-error-analysis/)
39. [**First Results in a Study Evaluating Pre-annotation and Correction Propagation for Machine-Assisted Syriac Morphological Analysis**Paul Felt, Eric Ringger, Kevin Seppi, et al.*2012 · 5 citations*](https://md.research.elamur.ai/free/en/papers/felt-2012-first-results-study-evaluating-pre/)
40. [**OasisSimp: An Open-source Asian-English Sentence Simplification Dataset**Hannah Liu, Murphy Tian, Iqra Ali, et al.*2026*](https://md.research.elamur.ai/free/en/papers/liu-2026-oasissimp-open-source-asian-english/)

644 more citing papers of our library have no page here yet.

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