---
title: "Who cites Strong Baselines for Neural — 63 citing papers"
description: "63 papers of the Elamur Research library cite «Strong Baselines for Neural Semi-Supervised Learning under Domain Shift», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/ruder-2018-strong-baselines-neural-semi-supervised/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ruder-2018-strong-baselines-neural-semi-supervised/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Strong Baselines for Neural Semi-Supervised…](https://md.research.elamur.ai/free/en/papers/ruder-2018-strong-baselines-neural-semi-supervised/) / cited by

# Who cites «Strong Baselines for Neural Semi-Supervised Learning under Domain Shift»

63 papers of our library cite it (of the 141,840 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «Strong Baselines for Neural Semi-Supervised Learning under Domain Shift»](https://md.research.elamur.ai/free/en/papers/ruder-2018-strong-baselines-neural-semi-supervised/)

1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,056 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
2. **[Semi-Supervised Sequence Modeling with Cross-View Training](https://md.research.elamur.ai/free/en/papers/clark-2018-semi-supervised-sequence-modeling-cross/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kevin Clark, Minh-Thang Luong, Christopher D. Manning, et al.*2018 · 491 citations*
3. **[Neural Unsupervised Domain Adaptation in NLP–-A Survey](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Alan Ramponi, Barbara Plank*2020 · 336 citations*
4. **[Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP](https://md.research.elamur.ai/free/en/papers/goot-2021-massive-choice-ample-tasks-machamp/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rob van der Goot, Ahmet Üstün, Alan Ramponi, et al.*2021 · 177 citations*
5. **[Synthetic Examples Improve Cross-Target Generalization: A Study on Stance Detection on a Twitter corpus.](https://md.research.elamur.ai/free/en/papers/conforti-2021-synthetic-examples-improve-cross-target/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar, et al.*2021 · 12 citations*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/ruder-2018-strong-baselines-neural-semi-supervised/) — Strong Baselines for Neural Semi-Supervised Learning under Domain Shift