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Much recent progress in applications of machine learning models to NLP has been driven by benchmarks that evaluate models across a wide variety of tasks.
Unsupervised multilingual grammar induction
Snyder, B., Naseem, T., and Barzilay, R · 2009
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Translationese and its dialects
Koppel, M. and Ordan, N · 2011
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Part-of-speech tagging from 97% to 100%: is it time for some linguistics?
Manning, C. D · 2011
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Multi-source transfer of delexicalized dependency parsers
McDonald, R., Petrov, S., and Hall, K · 2011
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Inducing Crosslingual Distributed Representations of Words
Klementiev, A., Titov, I., and Bhattarai, B · 2012
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Exploiting similarities among languages for machine translation
Mikolov, T., Le, Q. V., and Sutskever, I · 2013
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Token and Type Constraints for Cross-Lingual Part-of-Speech Tagging
Täckström, O., Das, D., Petrov, S., McDonald, R., and Nivre, J · 2013
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Improving vector space word representations using multilingual correlation
Faruqui, M. and Dyer, C · 2014
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BilBOWA: Fast bilingual distributed representations without word alignments
Gouws, S., Bengio, Y., and Corrado, G · 2015
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Bilingual word representations with monolingual quality in mind
Luong, T., Pham, H., and Manning, C. D · 2015
Earlier work this paper cites.
chrF: character n-gram f-score for automatic MT evaluation
Popović, M · 2015
Earlier work this paper cites.
How translation alters sentiment
Mohammad, S. M., Salameh, M., and Kiritchenko, S · 2016
Earlier work this paper cites.
SQuAD: 100,000+ Questions for Machine Comprehension of Text
Rajpurkar, P., Zhang, J., Lopyrev, K., and Liang, P · 2016
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Does ‘well-being’ translate on twitter?
Smith, L., Giorgi, S., Solanki, R., Eichstaedt, J., Schwartz, H. A., Abdul-Mageed, M., Buffone, A., and Ungar, L · 2016
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Learning bilingual word embeddings with (almost) no bilingual data
Artetxe, M., Labaka, G., and Agirre, E · 2017
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Learned in translation: Contextualized word vectors
McCann, B., Bradbury, J., Xiong, C., and Socher, R · 2017
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Cross-lingual name tagging and linking for 282 languages
Pan, X., Zhang, B., May, J., Nothman, J., Knight, K., and Ji, H · 2017
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Attention Is All You Need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
Earlier work this paper cites.
Earth mover’s distance minimization for unsupervised bilingual lexicon induction
Zhang, M., Liu, Y., Luan, H., and Sun, M · 2017
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Overview of the second bucc shared task: Spotting parallel sentences in comparable corpora
Zweigenbaum, P., Sharoff, S., and Rapp, R · 2017
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Baselines and test data for cross-lingual inference
Agić, Ž. and Schluter, N · 2018
Earlier work this paper cites.
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings
Artetxe, M., Labaka, G., and Agirre, E · 2018
Cited alongside, same era.
Bilingual sentiment embeddings: Joint projection of sentiment across languages
Barnes, J., Klinger, R., and Schulte im Walde, S · 2018
Cited alongside, same era.
Word translation without parallel data
Conneau, A., Lample, G., Ranzato, M., Denoyer, L., and Jégou, H · 2018
Cited alongside, same era.
XNLI: Evaluating cross-lingual sentence representations
Conneau, A., Rinott, R., Lample, G., Williams, A., Bowman, S., Schwenk, H., and Stoyanov, V · 2018
Cited alongside, same era.
Zero-shot cross-lingual classification using multilingual neural machine translation
Eriguchi, A., Johnson, M., Firat, O., Kazawa, H., and Macherey, W · 2018
Cited alongside, same era.
Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model
Hsu, T.-y., Liu, C.-l., and Lee, H.-y · 2019
Later among the works it cites.
Lost in evaluation: Misleading benchmarks for bilingual dictionary induction
Kementchedjhieva, Y., Hartmann, M., and Søgaard, A · 2019
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Cross-lingual Language Model Pretraining
Lample, G. and Conneau, A · 2019
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MLQA: Evaluating Cross-lingual Extractive Question Answering
Lewis, P., Oğuz, B., Rinott, R., Riedel, S., and Schwenk, H · 2019
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Choosing Transfer Languages for Cross-Lingual Learning
Lin, Y.-H., Chen, C.-Y., Lee, J., Li, Z., Zhang, Y., Xia, M., Rijhwani, S., He, J., Zhang, Z., Ma, X., Anastasopoulos, A., Littell, P., and Neubig, G · 2019
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Gururangan, S., Swayamdipta, S., Levy, O., Schwartz, R., Bowman, S. R., and Smith, N. A · 2018
Cited alongside, same era.
Universal language model fine-tuning for text classification
Howard, J. and Ruder, S · 2018
Cited alongside, same era.
Semi-supervised training data generation for multilingual question answering
Lee, K., Yoon, K., Park, S., and Hwang, S. W · 2018
Cited alongside, same era.
Universal dependencies 2.2
Nivre, J., Abrams, M., Agić, Ž., Ahrenberg, L., Antonsen, L., Aranzabe, M. J., Arutie, G., Asahara, M., Ateyah, L., Attia, M., et al · 2018
Cited alongside, same era.
Deep contextualized word representations
Peters, M., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., and Zettlemoyer, L · 2018
Cited alongside, same era.
A Corpus for Multilingual Document Classification in Eight Languages
Schwenk, H. and Li, X · 2018
Cited alongside, same era.
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Williams, A., Nangia, N., and Bowman, S. R · 2018
Cited alongside, same era.
Human vs. Muppet: A Conservative Estimate of Human Performance on the GLUE Benchmark
Nangia, N. and Bowman, S. R · 2019
Later among the works it cites.
How multilingual is Multilingual BERT?
Pires, T., Schlinger, E., and Garrette, D · 2019
Later among the works it cites.
Massively Multilingual Transfer for NER
Rahimi, A., Li, Y., and Cohn, T · 2019
Later among the works it cites.
A Survey of Cross-lingual Word Embedding Models
Ruder, S., Vulić, I., and Søgaard, A · 2019
Later among the works it cites.
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing
Schuster, T., Ram, O., Barzilay, R., and Globerson, A · 2019
Later among the works it cites.
Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?
Vulić, I., Glavaš, G., Reichart, R., and Korhonen, A · 2019
Later among the works it cites.
Superglue: A stickier benchmark for general-purpose language understanding systems
Wang, A., Pruksachatkun, Y., Nangia, N., Singh, A., Michael, J., Hill, F., Levy, O., and Bowman, S. R · 2019
Later among the works it cites.
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Wang, A., Singh, A., Michael, J., Hill, F., Levy, O., and Bowman, S. R · 2019
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Huggingface’s transformers: State-of-the-art natural language processing
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., et al · 2019
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Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT
Wu, S. and Dredze, M · 2019
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PAWS-X: A cross-lingual adversarial dataset for paraphrase identification
Yang, Y., Zhang, Y., Tar, C., and Baldridge, J · 2019
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PAWS: Paraphrase adversaries from word scrambling
Zhang, Y., Baldridge, J., and He, L · 2019
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On the Cross-lingual Transferability of Monolingual Representations
Artetxe, M., Ruder, S., and Yogatama, D · 2020
Closest in time.
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages
Clark, J. H., Choi, E., Collins, M., Garrette, D., Kwiatkowski, T., Nikolaev, V., and Palomaki, J · 2020
Closest in time.
Unsupervised Cross-lingual Representation Learning at Scale
Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., and Stoyanov, V · 2020
Closest in time.
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation
Siddhant, A., Johnson, M., Tsai, H., Arivazhagan, N., Riesa, J., Bapna, A., Firat, O., and Raman, K · 2020
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