🧑‍🔬 Who cites Thomas Hofmann

279 citations of their works from 278 papers of our library (of the 140,884 whose bibliographies we read) · 22 with a page here, the most cited first · ← Thomas Hofmann

1. Reading Tea Leaves: How Humans Interpret Topic ModelsJonathan Chang, Jordan Boyd-Graber, Sean Gerrish, et al.2009 · 2,037 citations
2. Opinion Word Expansion and Target Extraction through Double PropagationGuang Qiu, Bing Liu, Jiajun Bu, et al.2011 · 1,196 citations
3. AdapterFusion: Non-Destructive Task Composition for Transfer LearningJonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.2020 · 948 citations
4. Findings of the 2017 Conference on Machine Translation (WMT17)Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.2017 · 685 citations
5. Massively Multilingual Neural Machine Translation in the Wild: Findings and ChallengesNaveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.2019 · 555 citations
6. Improving Massively Multilingual Neural Machine Translation and Zero-Shot TranslationBiao Zhang, Philip Williams, Ivan Titov, et al.2020 · 472 citations
7. Meta-Learning for Low-Resource Neural Machine TranslationJiatao Gu, Yong Wang, Yun Chen, et al.2018 · 451 citations
8. Unsupervised Neural Machine TranslationMikel Artetxe, Gorka Labaka, Eneko Agirre, et al.2017 · 410 citations
9. Training Tips for the Transformer ModelMartin Popel, Ondřej Bojar2018 · 369 citations
10. A Latent Variable Model Approach to PMI-based Word EmbeddingsSanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.2016 · 365 citations
11. Universal Neural Machine Translation for Extremely Low Resource LanguagesJiatao Gu, Hany Hassan, Jacob Devlin, et al.2018 · 356 citations
12. Learning to Parse and Translate Improves Neural Machine TranslationAkiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho2017 · 214 citations
13. Charformer: Fast Character Transformers via Gradient-based Subword TokenizationYi Tay, Vinh Q. Tran, Sebastian Ruder, et al.2021 · 179 citations
14. Stronger Baselines for Trustable Results in Neural Machine TranslationMichael Denkowski, Graham Neubig2017 · 164 citations
15. Canine: Pre-training an Efficient Tokenization-Free Encoder for Language RepresentationJonathan H. Clark, Dan Garrette, Iulia Turc, et al.2022 · 156 citations
16. Language Model Tokenizers Introduce Unfairness Between LanguagesAleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.2023 · 149 citations
17. How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsRico Sennrich2017 · 147 citations
18. Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLPSabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.2021 · 89 citations
19. A Context-Theoretic Framework for Compositionality in Distributional SemanticsDaoud Clarke2012 · 83 citations
20. Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource SettingsPamela Shapiro, Kevin Duh2018 · 25 citations
21. Abstract Syntax as Interlingua: Scaling Up the Grammatical Framework from Controlled Languages to Robust PipelinesAarne Ranta, Krasimir Angelov, Normunds Gruzitis, et al.2020 · 21 citations
22. Comparing Pipelined and Integrated Approaches to Dialectal Arabic Neural Machine TranslationPamela Shapiro, Kevin Duh2019 · 5 citations

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

This page in Markdown → https://md.research.elamur.ai/free/en/authors/thomas-hofmann/cited-by/