---
title: "Who cites Johannes Leveling"
description: "466 papers of the Elamur Research library cite the works of Johannes Leveling, found in their bibliographies; the most cited first."
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---
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# Who cites Johannes Leveling

466 citations of their works from 466 papers of our library (of the 140,884 whose bibliographies we read) · 55 with a page here, the most cited first · [← Johannes Leveling](https://md.research.elamur.ai/free/en/authors/johannes-leveling/)

1. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 7,433 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
2. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
3. [**chrF: character n-gram F-score for automatic MT evaluation**Maja Popović*2015 · 2,105 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/)
4. [**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/)
5. [**Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm**Laria Reynolds, Kyle McDonell*2021 · 1,111 citations*](https://md.research.elamur.ai/free/en/papers/reynolds-2021-prompt-programming-large-language-models/)
6. [**RoFormer: Enhanced Transformer with Rotary Position Embedding**Jianlin Su, Yu Lu, Shengfeng Pan, et al.*2021 · 1,072 citations*](https://md.research.elamur.ai/free/en/papers/su-2021-roformer-enhanced-transformer-rotary-position/)
7. [**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/)
8. [**SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation**Daniel Cer, Mona Diab, Eneko Agirre, et al.*2017 · 907 citations*](https://md.research.elamur.ai/free/en/papers/cer-2017-semeval-2017-task-1-semantic/)
9. [**Findings of the 2019 Conference on Machine Translation (WMT19)**Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al.*2019 · 839 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/)
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. [**How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation**Chia-Wei Liu, Ryan Lowe, Iulian Serban, et al.*2016 · 500 citations*](https://md.research.elamur.ai/free/en/papers/liu-2016-how-not-evaluate-your-dialogue/)
13. [**Findings of the 2015 Workshop on Statistical Machine Translation**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2015 · 461 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2015-findings-2015-workshop-statistical-machine/)
14. [**C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models**Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-c-eval-multi-level-multi/)
15. [**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/)
16. [**Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages**Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, et al.*2022 · 307 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2022-samanantar-largest-publicly-available-parallel/)
17. [**SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer**Tu Vu, Brian Lester, Noah Constant, et al.*2022 · 300 citations*](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/)
18. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
19. [**Adaptively Sparse Transformers**Gonçalo M. Correia, Vlad Niculae, André F. T. Martins*2019 · 270 citations*](https://md.research.elamur.ai/free/en/papers/correia-2019-adaptively-sparse-transformers/)
20. [**CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review**Dan Hendrycks, Collin Burns, Anya Chen, et al.*2021 · 265 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-cuad-expert-annotated-nlp-dataset/)
21. [**Multilingual Translation from Denoising Pre-Training**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 219 citations*](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/)
22. [**IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages**Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.*2023 · 200 citations*](https://md.research.elamur.ai/free/en/papers/gala-2023-indictrans2-towards-high-quality-accessible/)
23. [**End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification**Jindřich Libovický, Jindřich Helcl*2018 · 200 citations*](https://md.research.elamur.ai/free/en/papers/libovicky-2018-end-end-non-autoregressive-neural/)
24. [**A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/)
25. [**Report on the 11th IWSLT evaluation campaign**Mauro Cettolo, Jan Niehues, Sebastian Stüker, et al.*2014 · 193 citations*](https://md.research.elamur.ai/free/en/papers/cettolo-2014-report-11th-iwslt-evaluation-campaign/)
26. [**Findings of the 2021 Conference on Machine Translation (WMT21)**Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, et al.*2021 · 189 citations*](https://md.research.elamur.ai/free/en/papers/akhbardeh-2021-findings-2021-conference-machine-translation/)
27. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
28. [**Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP**Rob van der Goot, Ahmet Üstün, Alan Ramponi, et al.*2021 · 177 citations*](https://md.research.elamur.ai/free/en/papers/goot-2021-massive-choice-ample-tasks-machamp/)
29. [**The IIT Bombay English-Hindi Parallel Corpus**Anoop Kunchukuttan, Pratik Mehta, Pushpak Bhattacharyya*2018 · 174 citations*](https://md.research.elamur.ai/free/en/papers/kunchukuttan-2018-iit-bombay-english-hindi-parallel/)
30. [**Results of the WMT14 Metrics Shared Task**Matouš Macháček, Ondřej Bojar*2014 · 174 citations*](https://md.research.elamur.ai/free/en/papers/machacek-2014-results-wmt14-metrics-shared-task/)
31. [**Probing What Different NLP Tasks Teach Machines about Function Word Comprehension**Najoung Kim, Roma Patel, Adam Poliak, et al.*2019 · 161 citations*](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/)
32. [**Accurate Evaluation of Segment-level Machine Translation Metrics**Yvette Graham, Timothy Baldwin, Nitika Mathur*2015 · 155 citations*](https://md.research.elamur.ai/free/en/papers/graham-2015-accurate-evaluation-segment-level-machine/)
33. [**Statistical Power and Translationese in Machine Translation Evaluation**Yvette Graham, Barry Haddow, Philipp Koehn*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/graham-2020-statistical-power-translationese-machine-translation/)
34. [**Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation**Jungo Kasai, Nikolaos Pappas, Hao Peng, et al.*2020 · 132 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2020-deep-encoder-shallow-decoder-reevaluating/)
35. [**GlotLID: Language Identification for Low-Resource Languages**Amir Hossein Kargaran, Ayyoob Imani, François Yvon, et al.*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/kargaran-2023-glotlid-language-identification-low-resource/)
36. [**MEANT 2.0: Accurate semantic MT evaluation for any output language**Chi-kiu Lo*2017 · 81 citations*](https://md.research.elamur.ai/free/en/papers/lo-2017-meant-2-0-accurate-semantic/)
37. [**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/)
38. [**chrF deconstructed: beta parameters and n-gram weights**Maja Popović*2016 · 76 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2016-chrf-deconstructed-beta-parameters-n/)
39. [**Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/)
40. [**Tokenization Is More Than Compression**Craig W Schmidt, Varshini Reddy, Haoran Zhang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2024-tokenization-is-more-than-compression/)
41. [**An Open Dataset and Model for Language Identification**Laurie Burchell, Alexandra Birch, Nikolay Bogoychev, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/burchell-2023-open-dataset-model-language-identification/)
42. [**HUME: Human UCCA-Based Evaluation of Machine Translation**Alexandra Birch, Omri Abend, Ondřej Bojar, et al.*2016 · 58 citations*](https://md.research.elamur.ai/free/en/papers/birch-2016-hume-human-ucca-based-evaluation/)
43. [**Automatic Evaluation and Analysis of Idioms in Neural Machine Translation**Christos Baziotis, Prashant Mathur, Eva Hasler*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/baziotis-2023-automatic-evaluation-analysis-idioms-neural/)
44. [**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/)
45. [**Beyond Random Sampling: Efficient Language Model Pretraining via Curriculum Learning**Yang Zhang, Amr Mohamed, Hadi Abdine, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-random-sampling-efficient-language/)
46. [**Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models**Mohamed Taher Alrefaie, Nour Eldin Morsy, Nada Samir*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/alrefaie-2024-exploring-tokenization-strategies-vocabulary-sizes/)
47. [**Predicting and Using a Pragmatic Component of Lexical Aspect of Simple Past Verbal Tenses for Improving English-to-French Machine Translation**Sharid Loáiciga, Cristina Grisot*2016 · 5 citations*](https://md.research.elamur.ai/free/en/papers/loaiciga-2016-predicting-pragmatic-component-lexical-aspect/)
48. [**Kuwain 1.5B: An Arabic SLM via Language Injection**Khalil Hennara, Sara Chrouf, Mohamed Motaism Hamed, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-kuwain-1-5b-arabic-slm/)
49. [**MoVoC: Morphology-Aware Subword Construction for Ge'ez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction/)
50. [**MoVoC: Morphology-Aware Subword Construction for Geez Script Languages**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2025-movoc-morphology-aware-subword-construction-geez/)
51. [**Do Diacritics Matter? Evaluating the Impact of Arabic Diacritics on Tokenization and LLM Benchmarks**Go Inoue, Bashar Alhafni, Nizar Habash, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2026-do-diacritics-matter-evaluating-impact/)
52. [**Morphemes Without Borders: Evaluating Root-Pattern Morphology in Arabic Tokenizers and LLMs**Yara Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-borders-evaluating-root-pattern/)
53. [**Morphemes without Borders: Evaluating Root–Pattern Morphology in Arabic Tokenizers and LLMs**Yara Yousif Alakeel, Chatrine Qwaider, Hanan Aldarmaki, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alakeel-2026-morphemes-without-borders-evaluating-root/)
54. [**When Alignment Hurts: Decoupling Representational Spaces in Multilingual Models**Ahmed Elshabrawy, Hour Kaing, Haiyue Song, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elshabrawy-2025-alignment-hurts-decoupling-representational-spaces/)
55. [**A Single Model Ensemble Framework for Neural Machine Translation Using Pivot Translation**Seokjin Oh, Keonwoong Noh, Woohwan Jung*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-single-model-ensemble-framework-neural/)

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

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