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List of Annotated Papers

Abdellatif, M., & Elgammal, A. (2020). ULMFiT replication. Proceedings of the 12th Language Resources and Evaluation Conference, 5579–5587. https://www.aclweb.org/anthology/2020.lrec-1.685

António Rodrigues, J., Branco, R., Silva, J., & Branco, A. (2020). Reproduction and revival of the argument reasoning comprehension task. Proceedings of the 12th Language Resources and Evaluation Conference, 5055–5064. https://www.aclweb.org/anthology/2020.lrec-1.622

Arhiliuc, C., Mitrović, J., & Granitzer, M. (2020). Language proficiency scoring. Proceedings of the 12th Language Resources and Evaluation Conference, 5624–5630. https://www.aclweb.org/anthology/2020.lrec-1.690

Bestgen, Y. (2020). Reproducing monolingual, multilingual and cross-lingual CEFR predictions. Proceedings of the 12th Language Resources and Evaluation Conference, 5595–5602. https://www.aclweb.org/anthology/2020.lrec-1.687

Born, L., Bacher, M., & Markert, K. (2020). Dataset reproducibility and IR methods in timeline summarization. Proceedings of the 12th Language Resources and Evaluation Conference, 1763–1771. https://www.aclweb.org/anthology/2020.lrec-1.218

Branco, A. (2018, May). We are depleting our research subject as we are investigating it: In language technology, more replication and diversity are needed. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). https://www.aclweb.org/anthology/L18-1022

Branco, A., Calzolari, N., Vossen, P., Van Noord, G., Uytvanck, D. van, Silva, J., Gomes, L., Moreira, A., & Elbers, W. (2020). A shared task of a new, collaborative type to foster reproducibility: A first exercise in the area of language science and technology with REPROLANG2020. Proceedings of the 12th Language Resources and Evaluation Conference, 5539–5545. https://www.aclweb.org/anthology/2020.lrec-1.680

Caines, A., & Buttery, P. (2020). REPROLANG 2020: Automatic proficiency scoring of Czech, English, German, Italian, and Spanish learner essays. Proceedings of the 12th Language Resources and Evaluation Conference, 5614–5623. https://www.aclweb.org/anthology/2020.lrec-1.689

Cohen, K. B., Xia, J., Zweigenbaum, P., Callahan, T., Hargraves, O., Goss, F., Ide, N., Névéol, A., Grouin, C., & Hunter, L. E. (2018, May). Three dimensions of reproducibility in natural language processing. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). https://www.aclweb.org/anthology/L18-1025

Cooper, M., & Shardlow, M. (2020). CombiNMT: An exploration into neural text simplification models. Proceedings of the 12th Language Resources and Evaluation Conference, 5588–5594. https://www.aclweb.org/anthology/2020.lrec-1.686

Crane, M. (2018). Questionable answers in question answering research: Reproducibility and variability of published results. Transactions of the Association for Computational Linguistics, 6, 241–252. https://doi.org/10.1162/tacl_a_00018

Dakota, D., & Kübler, S. (2017). Towards replicability in parsing. Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017, 185–194. https://doi.org/10.26615/978-954-452-049-6_026

Fares, M., Kutuzov, A., Oepen, S., & Velldal, E. (2017). Word vectors, reuse, and replicability: Towards a community repository of large-text resources. Proceedings of the 21st Nordic Conference on Computational Linguistics, 271–276. https://www.aclweb.org/anthology/W17-0237

Fokkens, A., Erp, M. van, Postma, M., Pedersen, T., Vossen, P., & Freire, N. (2013). Offspring from reproduction problems: What replication failure teaches us. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 1691–1701. https://www.aclweb.org/anthology/P13-1166

Fortuna, P., Soler-Company, J., & Nunes, S. (2019). Stop PropagHate at SemEval-2019 tasks 5 and 6: Are abusive language classification results reproducible? Proceedings of the 13th International Workshop on Semantic Evaluation, 745–752. https://doi.org/10.18653/v1/S19-2131

Garneau, N., Godbout, M., Beauchemin, D., Durand, A., & Lamontagne, L. (2020). A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings: Making the method robustly reproducible as well. Proceedings of the 12th Language Resources and Evaluation Conference, 5546–5554. https://www.aclweb.org/anthology/2020.lrec-1.681

Gärtner, M., Hahn, U., & Hermann, S. (2018, May). Preserving workflow reproducibility: The RePlay-DH client as a tool for process documentation. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). https://www.aclweb.org/anthology/L18-1089

Horsmann, T., & Zesch, T. (2018, May). DeepTC – an extension of DKPro text classification for fostering reproducibility of deep learning experiments. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). https://www.aclweb.org/anthology/L18-1403

Horsmann, T., & Zesch, T. (2017). Do LSTMs really work so well for PoS tagging? – a replication study. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 727–736. https://doi.org/10.18653/v1/D17-1076

Htut, P. M., Cho, K., & Bowman, S. (2018a). Grammar induction with neural language models: An unusual replication. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 371–373. https://doi.org/10.18653/v1/W18-5452

Htut, P. M., Cho, K., & Bowman, S. (2018b). Grammar induction with neural language models: An unusual replication. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 4998–5003. https://doi.org/10.18653/v1/D18-1544

Huber, E., & Çöltekin, Ç. (2020). Reproduction and replication: A case study with automatic essay scoring. Proceedings of the 12th Language Resources and Evaluation Conference, 5603–5613. https://www.aclweb.org/anthology/2020.lrec-1.688

Khoe, Y. H. (2020). Reproducing a morphosyntactic tagger with a meta-BiLSTM model over context sensitive token encodings. Proceedings of the 12th Language Resources and Evaluation Conference, 5563–5568. https://www.aclweb.org/anthology/2020.lrec-1.683

Mieskes, M., Fort, K., Névéol, A., Grouin, C., & Cohen, K. (2019). Community perspective on replicability in natural language processing. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), 768–775. https://doi.org/10.26615/978-954-452-056-4_089

Millour, A., Fort, K., & Magistry, P. (2020). Répliquer et étendre pour l’alsacien “Étiquetage en parties du discours de langues peu dotées par spécialisation des plongements lexicaux” (replicating and extending for Alsatian : “POS tagging for low-resource languages by adapting word embeddings”). Actes de La 6e Conférence Conjointe Journées d’Études Sur La Parole (JEP, 33e édition), Traitement Automatique Des Langues Naturelles (TALN, 27e édition), Rencontre Des Étudiants Chercheurs En Informatique Pour Le Traitement Automatique Des Langues (rÉCITAL, 22e édition). 2e Atelier Éthique Et TRaitemeNt Automatique Des Langues (ETeRNAL), 29–37. https://www.aclweb.org/anthology/2020.jeptalnrecital-eternal.4

Miltenburg, E. van, Kerkhof, M. van de, Koolen, R., Goudbeek, M., & Krahmer, E. (2019). On task effects in NLG corpus elicitation: A replication study using mixed effects modeling. Proceedings of the 12th International Conference on Natural Language Generation, 403–408. https://doi.org/10.18653/v1/W19-8649

Moore, A., & Rayson, P. (2018). Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for target dependent sentiment analysis. Proceedings of the 27th International Conference on Computational Linguistics, 1132–1144. https://www.aclweb.org/anthology/C18-1097

Morey, M., Muller, P., & Asher, N. (2017). How much progress have we made on RST discourse parsing? A replication study of recent results on the RST-DT. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 1319–1324. https://doi.org/10.18653/v1/D17-1136

Névéol, A., Cohen, K., Grouin, C., & Robert, A. (2016). Replicability of research in biomedical natural language processing: A pilot evaluation for a coding task. Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis, 78–84. https://doi.org/10.18653/v1/W16-6110

Pluciński, K., Lango, M., & Zimniewicz, M. (2020). A closer look on unsupervised cross-lingual word embeddings mapping. Proceedings of the 12th Language Resources and Evaluation Conference, 5555–5562. https://www.aclweb.org/anthology/2020.lrec-1.682

Rim, K., Tu, J., Lynch, K., & Pustejovsky, J. (2020). Reproducing neural ensemble classifier for semantic relation extraction inScientific papers. Proceedings of the 12th Language Resources and Evaluation Conference, 5569–5578. https://www.aclweb.org/anthology/2020.lrec-1.684

Schwartz, L. (2010). Reproducible results in parsing-based machine translation: The JHU shared task submission. Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR, 177–182. https://www.aclweb.org/anthology/W10-1726

Wieling, M., Rawee, J., & Noord, G. van. (2018). Squib: Reproducibility in computational linguistics: Are we willing to share? Computational Linguistics, 44(4), 641–649. https://doi.org/10.1162/coli_a_00330

Wu, T., Ribeiro, M. T., Heer, J., & Weld, D. (2019). Errudite: Scalable, reproducible, and testable error analysis. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 747–763. https://doi.org/10.18653/v1/P19-1073

Zhang, X., & Duh, K. (2020). Reproducible and efficient benchmarks for hyperparameter optimization of neural machine translation systems. Transactions of the Association for Computational Linguistics, 8, 393–408. https://doi.org/10.1162/tacl_a_00322