--- title: "Natural language processing — papers, page 49" description: "Natural language processing: 2421 papers of the Elamur Research library · page 49 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/49/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/49/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Natural language processing](https://md.research.elamur.ai/free/en/shelves/nlp/) / page 49 # 💬 Natural language processing 2421 papers · page 49 of 97 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Computational linguistics from the ACL Anthology and arXiv: language models, information extraction, dialogue, evaluation. [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/48/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [48](https://md.research.elamur.ai/free/en/shelves/nlp/page/48/) **49** [50](https://md.research.elamur.ai/free/en/shelves/nlp/page/50/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/50/) - [JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/agic-2019-jw300-wide-coverage-parallel-corpus/) — Željko Agić, Ivan Vulić · 2019 - [Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/) — Peixiang Zhong, Di Wang, Chunyan Miao · 2019 - [Large-Scale Multi-Label Text Classification on EU Legislation](https://md.research.elamur.ai/free/en/papers/chalkidis-2019-large-scale-multi-label-text/) — Ilias Chalkidis, Emmanouil Fergadiotis, Prodromos Malakasiotis, et al. · 2019 - [Latent Retrieval for Weakly Supervised Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/lee-2019-latent-retrieval-weakly-supervised-open/) — Kenton Lee, Ming-Wei Chang, Kristina Toutanova · 2019 - [Learning Deep Transformer Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-learning-deep-transformer-models-machine/) — Qiang Wang, Bei Li, Tong Xiao, et al. · 2019 - [Learning Dense Representations for Entity Retrieval](https://md.research.elamur.ai/free/en/papers/gillick-2019-learning-dense-representations-entity-retrieval/) — Daniel Gillick, Sayali Kulkarni, Larry Lansing, et al. · 2019 - [Linguistic Knowledge and Transferability of Contextual Representations](https://md.research.elamur.ai/free/en/papers/liu-2019-linguistic-knowledge-transferability-contextual-representations/) — Nelson F. Liu, Matt Gardner, Yonatan Belinkov, et al. · 2019 - [Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them](https://md.research.elamur.ai/free/en/papers/gonen-2019-lipstick-pig-debiasing-methods-cover/) — Hila Gonen, Yoav Goldberg · 2019 - [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://md.research.elamur.ai/free/en/papers/tan-2019-lxmert-learning-cross-modality-encoder/) — Hao Tan, Mohit Bansal · 2019 - [Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/artetxe-2019-margin-based-parallel-corpus-mining/) — Mikel Artetxe, Holger Schwenk · 2019 - [Mask-Predict: Parallel Decoding of Conditional Masked Language Models](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/) — Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al. · 2019 - [Massively Multilingual Transfer for NER](https://md.research.elamur.ai/free/en/papers/rahimi-2019-massively-multilingual-transfer-ner/) — Afshin Rahimi, Yuan Li, Trevor Cohn · 2019 - [Measuring Bias in Contextualized Word Representations](https://md.research.elamur.ai/free/en/papers/kurita-2019-measuring-bias-contextualized-word-representations/) — Keita Kurita, Nidhi Vyas, Ayush Pareek, et al. · 2019 - [Mitigating Gender Bias in Natural Language Processing: Literature Review](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/) — Tony Sun, Andrew Gaut, Shirlyn Tang, et al. · 2019 - [Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ponti-2019-modeling-language-variation-universals-survey/) — Edoardo Maria Ponti, Helen O'Horan, Yevgeni Berzak, et al. · 2019 - [MoEL: Mixture of Empathetic Listeners](https://md.research.elamur.ai/free/en/papers/lin-2019-moel-mixture-empathetic-listeners/) — Zhaojiang Lin, Andrea Madotto, Jamin Shin, et al. · 2019 - [Monotonic Infinite Lookback Attention for Simultaneous Machine Translation](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-monotonic-infinite-lookback-attention-simultaneous/) — Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, et al. · 2019 - [Morphologically Annotated Corpora for Seven Arabic Dialects: Taizi, Sanaani, Najdi, Jordanian, Syrian, Iraqi and Moroccan](https://md.research.elamur.ai/free/en/papers/aclbulk-2019-alshargi-morphologically-annotated-corpora-seven-arabic/) — Faisal Alshargi, Shahd Dibas, Sakhar Alkhereyf, et al. · 2019 - [MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance](https://md.research.elamur.ai/free/en/papers/zhao-2019-moverscore-text-generation-evaluating-contextualized/) — Wei Zhao, Maxime Peyrard, Fei Liu, et al. · 2019 - [MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension](https://md.research.elamur.ai/free/en/papers/fisch-2019-mrqa-2019-shared-task-evaluating/) — Adam Fisch, Alon Talmor, Robin Jia, et al. · 2019 - [Multi-hop Reading Comprehension through Question Decomposition and Rescoring](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/) — Sewon Min, Victor Zhong, Luke Zettlemoyer, et al. · 2019 - [Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model](https://md.research.elamur.ai/free/en/papers/fabbri-2019-multi-news-large-scale-multi/) — Alexander Fabbri, Irene Li, Tianwei She, et al. · 2019 - [Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2019-multi-passage-bert-globally-normalized/) — Zhiguo Wang, Patrick Ng, Xiaofei Ma, et al. · 2019 - [Multi-Task Deep Neural Networks for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/) — Xiaodong Liu, Pengcheng He, Weizhu Chen, et al. · 2019 - [MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/) — Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al. · 2019 [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/48/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [48](https://md.research.elamur.ai/free/en/shelves/nlp/page/48/) **49** [50](https://md.research.elamur.ai/free/en/shelves/nlp/page/50/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/50/)