---
title: "Who cites Ramón Fernandez Astudillo"
description: "467 papers of the Elamur Research library cite the works of Ramón Fernandez Astudillo, found in their bibliographies; the most cited first."
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---
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# Who cites Ramón Fernandez Astudillo

583 citations of their works from 467 papers of our library (of the 140,884 whose bibliographies we read) · 55 with a page here, the most cited first · [← Ramón Fernandez Astudillo](https://md.research.elamur.ai/free/en/authors/ramon-fernandez-astudillo/)

1. [**Hierarchical Attention Networks for Document Classification**Zichao Yang, Diyi Yang, Chris Dyer, et al.*2016 · 5,409 citations*](https://md.research.elamur.ai/free/en/papers/yang-2016-hierarchical-attention-networks-document-classification/)
2. [**Neural Machine Translation of Rare Words with Subword Units**Rico Sennrich, Barry Haddow, Alexandra Birch*2016 · 3,409 citations*](https://md.research.elamur.ai/free/en/papers/sennrich-2016-neural-machine-translation-rare-words/)
3. [**Deep Contextualized Word Representations**Matthew E. Peters, Mark Neumann, Mohit Iyyer, et al.*2018 · 3,240 citations*](https://md.research.elamur.ai/free/en/papers/peters-2018-deep-contextualized-word-representations/)
4. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
5. [**Enriching Word Vectors with Subword Information**Piotr Bojanowski, Edouard Grave, Armand Joulin, et al.*2017 · 2,218 citations*](https://md.research.elamur.ai/free/en/papers/bojanowski-2017-enriching-word-vectors-subword-information/)
6. [**Character-Aware Neural Language Models**Yoon Kim, Yacine Jernite, David Sontag, et al.*2015 · 1,852 citations*](https://md.research.elamur.ai/free/en/papers/kim-2015-character-aware-neural-language-models/)
7. [**COMET: A Neural Framework for MT Evaluation**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 1,784 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)
8. [**Findings of the 2016 Conference on Machine Translation**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2016 · 936 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2016-findings-2016-conference-machine-translation/)
9. [**End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF**Xuezhe Ma, Eduard Hovy*2016 · 852 citations*](https://md.research.elamur.ai/free/en/papers/ma-2016-end-end-sequence-labeling-bi/)
10. [**Findings of the 2018 Conference on Machine Translation (WMT18)**Ondřej Bojar, Christian Federmann, Mark Fishel, et al.*2018 · 747 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2018-findings-2018-conference-machine-translation/)
11. [**Findings of the 2017 Conference on Machine Translation (WMT17)**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2017 · 685 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/)
12. [**Globally Normalized Transition-Based Neural Networks**Daniel Andor, Chris Alberti, David Weiss, et al.*2016 · 676 citations*](https://md.research.elamur.ai/free/en/papers/andor-2016-globally-normalized-transition-based-neural/)
13. [**A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 666 citations*](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/)
14. [**A Survey on Recent Advances in Named Entity Recognition from Deep Learning models**Vikas Yadav, Steven Bethard*2018 · 565 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2018-survey-recent-advances-named-entity/)
15. [**Fast and Accurate Entity Recognition with Iterated Dilated Convolutions**Emma Strubell, Patrick Verga, David Belanger, et al.*2017 · 544 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2017-fast-accurate-entity-recognition-iterated/)
16. [**Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models**Minh-Thang Luong, Christopher D. Manning*2016 · 469 citations*](https://md.research.elamur.ai/free/en/papers/luong-2016-achieving-open-vocabulary-neural-machine/)
17. [**75 Languages, 1 Model: Parsing Universal Dependencies Universally**Dan Kondratyuk, Milan Straka*2019 · 415 citations*](https://md.research.elamur.ai/free/en/papers/kondratyuk-2019-75-languages-1-model-parsing/)
18. [**A Character-level Decoder without Explicit Segmentation for Neural Machine Translation**Junyoung Chung, Kyunghyun Cho, Yoshua Bengio*2016 · 407 citations*](https://md.research.elamur.ai/free/en/papers/chung-2016-character-level-decoder-without-explicit/)
19. [**Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs**Miguel Ballesteros, Chris Dyer, Noah A. Smith*2015 · 401 citations*](https://md.research.elamur.ai/free/en/papers/ballesteros-2015-improved-transition-based-parsing-modeling/)
20. [**Neural Architectures for Nested NER through Linearization**Jana Straková, Milan Straka, Jan Hajic*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/strakova-2019-neural-architectures-nested-ner-through/)
21. [**Stanford's Graph-based Neural Dependency Parser at the CoNLL 2017 Shared Task**Timothy Dozat, Peng Qi, Christopher D. Manning*2017 · 346 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2017-stanford-s-graph-based-neural/)
22. [**UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task**Milan Straka*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/straka-2018-udpipe-2-0-prototype-conll/)
23. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought**Abulhair Saparov, He He*2022 · 238 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/)
24. [**Commonsense Knowledge Base Completion**Xiang Li, Aynaz Taheri, Lifu Tu, et al.*2016 · 232 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-commonsense-knowledge-base-completion/)
25. [**Detecting Hallucinated Content in Conditional Neural Sequence Generation**Chunting Zhou, Graham Neubig, Jiatao Gu, et al.*2021 · 229 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/)
26. [**OpenKiwi: An Open Source Framework for Quality Estimation**Fabio Kepler, Jonay Trénous, Marcos Treviso, et al.*2019 · 215 citations*](https://md.research.elamur.ai/free/en/papers/kepler-2019-openkiwi-open-source-framework-quality/)
27. [**Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss**Barbara Plank, Anders Søgaard, Yoav Goldberg*2016 · 201 citations*](https://md.research.elamur.ai/free/en/papers/plank-2016-multilingual-part-speech-tagging-bidirectional/)
28. [**Data Augmentation via Dependency Tree Morphing for Low-Resource Languages**Gözde Gül Şahin, Mark Steedman*2018 · 166 citations*](https://md.research.elamur.ai/free/en/papers/sahin-2018-data-augmentation-dependency-tree-morphing/)
29. [**Graph Pre-training for AMR Parsing and Generation**Xuefeng Bai, Yulong Chen, Yue Zhang*2022 · 153 citations*](https://md.research.elamur.ai/free/en/papers/bai-2022-graph-pre-training-amr-parsing/)
30. [**Investigating Pretrained Language Models for Graph-to-Text Generation**Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.*2021 · 149 citations*](https://md.research.elamur.ai/free/en/papers/ribeiro-2021-investigating-pretrained-language-models-graph/)
31. [**Findings of the WMT 2018 Shared Task on Quality Estimation**Lucia Specia, Frédéric Blain, Varvara Logacheva, et al.*2018 · 134 citations*](https://md.research.elamur.ai/free/en/papers/specia-2018-findings-wmt-2018-shared-task/)
32. [**LSTM CCG Parsing**Mike Lewis, Kenton Lee, Luke Zettlemoyer*2016 · 120 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2016-lstm-ccg-parsing/)
33. [**TransQuest: Translation Quality Estimation with Cross-lingual Transformers**Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov*2020 · 91 citations*](https://md.research.elamur.ai/free/en/papers/ranasinghe-2020-transquest-translation-quality-estimation-cross/)
34. [**Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP**Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.*2021 · 89 citations*](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/)
35. [**Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/)
36. [**MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset**Marina Fomicheva, Shuo Sun, Erick Fonseca, et al.*2022 · 76 citations*](https://md.research.elamur.ai/free/en/papers/fomicheva-2022-mlqe-pe-multilingual-quality-estimation/)
37. [**Towards a Decomposable Metric for Explainable Evaluation of Text Generation from AMR**Juri Opitz, Anette Frank*2021 · 50 citations*](https://md.research.elamur.ai/free/en/papers/opitz-2021-decomposable-metric-explainable-evaluation-text/)
38. [**Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity**Juri Opitz, Angel Daza, Anette Frank*2021 · 47 citations*](https://md.research.elamur.ai/free/en/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/)
39. [**Implicit Discourse Relation Recognition with Context-aware Character-enhanced Embeddings**Lianhui Qin, Zhisong Zhang, Hai Zhao*2016 · 46 citations*](https://md.research.elamur.ai/free/en/papers/qin-2016-implicit-discourse-relation-recognition-context/)
40. [**Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew**Adam Amram, Anat Ben David, Reut Tsarfaty*2018 · 40 citations*](https://md.research.elamur.ai/free/en/papers/amram-2018-representations-architectures-neural-sentiment-analysis/)
41. [**From Shakespeare to Twitter: What are Language Styles all about?**Wei Xu*2017 · 29 citations*](https://md.research.elamur.ai/free/en/papers/xu-2017-shakespeare-twitter-what-are-language/)
42. [**Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings**Pamela Shapiro, Kevin Duh*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/shapiro-2018-morphological-word-embeddings-arabic-neural/)
43. [**DocAMR: Multi-Sentence AMR Representation and Evaluation**Tahira Naseem, Austin Blodgett, Sadhana Kumaravel, et al.*2022 · 24 citations*](https://md.research.elamur.ai/free/en/papers/naseem-2022-docamr-multi-sentence-amr-representation/)
44. [**A Human Evaluation of AMR-to-English Generation Systems**Emma Manning, Shira Wein, Nathan Schneider*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/manning-2020-human-evaluation-amr-english-generation/)
45. [**A Pointer Network Architecture for Joint Morphological Segmentation and Tagging**Amit Seker, Reut Tsarfaty*2020 · 21 citations*](https://md.research.elamur.ai/free/en/papers/seker-2020-pointer-network-architecture-joint-morphological/)
46. [**Assessing the Cross-linguistic Utility of Abstract Meaning Representation**Shira Wein, Nathan Schneider*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/wein-2024-assessing-cross-linguistic-utility-abstract/)
47. [**Evaluating Text Generation from Discourse Representation Structures**Chunliu Wang, Rik van Noord, Arianna Bisazza, et al.*2021 · 14 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-evaluating-text-generation-discourse-representation/)
48. [**AMR-TST: Abstract Meaning Representation-based Text Style Transfer**Kaize Shi, Xueyao Sun, Li He, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-amr-tst-abstract-meaning-representation/)
49. [**Survey of Abstract Meaning Representation: Then, Now, Future**Behrooz Mansouri*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/mansouri-2025-survey-abstract-meaning-representation-then/)
50. [**A Neural Model for Part-of-Speech Tagging in Historical Texts**Christian Hardmeier*2016 · 7 citations*](https://md.research.elamur.ai/free/en/papers/hardmeier-2016-neural-model-part-speech-tagging/)
51. [**Experiments in Cuneiform Language Identification**Gustavo Henrique Paetzold, Marcos Zampieri*2019 · 6 citations*](https://md.research.elamur.ai/free/en/papers/paetzold-2019-experiments-cuneiform-language-identification/)
52. [**Bridging Semantic Frameworks: mapping DRS onto AMR**Siyana Pavlova, Maxime Amblard, Bruno Guillaume*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/pavlova-2023-bridging-semantic-frameworks-mapping-drs/)
53. [**Generating Text from Uniform Meaning Representation**Emma Markle, Reihaneh Iranmanesh, Shira Wein*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/markle-2025-generating-text-uniform-meaning-representation/)
54. [**Modelling Idiomatic Expressions in Abstract Meaning Representation**Venera Gareeva, Johannes Heinecke*2026*](https://md.research.elamur.ai/free/en/papers/gareeva-2026-modelling-idiomatic-expressions-abstract-meaning/)
55. [**Syntax is the Key to Semantics: Combining Universal Dependencies and Abstract Meaning Representation**Johannes Heinecke*2026*](https://md.research.elamur.ai/free/en/papers/heinecke-2026-syntax-is-key-semantics-combining/)

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

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