--- title: "Natural language processing — papers, page 39" description: "Natural language processing: 2421 papers of the Elamur Research library · page 39 of 97 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/nlp/page/39/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/nlp/page/39/) [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 39 # 💬 Natural language processing 2421 papers · page 39 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/38/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [38](https://md.research.elamur.ai/free/en/shelves/nlp/page/38/) **39** [40](https://md.research.elamur.ai/free/en/shelves/nlp/page/40/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/40/) - [Extracting Headless MWEs from Dependency Parse Trees: Parsing, Tagging, and Joint Modeling Approaches](https://md.research.elamur.ai/free/en/papers/acl-2020-shi-extracting-headless-mwes-dependency-parse/) — Tianze Shi, Lillian Lee · 2020 - [Extractive Summarization as Text Matching](https://md.research.elamur.ai/free/en/papers/zhong-2020-extractive-summarization-as-text-matching/) — Ming Zhong, Pengfei Liu, Yiran Chen, et al. · 2020 - [Fact or Fiction: Verifying Scientific Claims](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/) — David Wadden, Shanchuan Lin, Kyle Lo, et al. · 2020 - [Factual Error Correction for Abstractive Summarization Models](https://md.research.elamur.ai/free/en/papers/cao-2020-factual-error-correction-abstractive-summarization/) — Meng Cao, Yue Dong, Jiapeng Wu, et al. · 2020 - [Fairseq S2T: Fast Speech-to-Text Modeling with Fairseq](https://md.research.elamur.ai/free/en/papers/wang-2020-fairseq-s2t-fast-speech-text/) — Changhan Wang, Yun Tang, Xutai Ma, et al. · 2020 - [Fast and Accurate Non-Projective Dependency Tree Linearization](https://md.research.elamur.ai/free/en/papers/yu-2020-fast-accurate-non-projective-dependency/) — Xiang Yu, Simon Tannert, Ngoc Thang Vu, et al. · 2020 - [FastBERT: a Self-distilling BERT with Adaptive Inference Time](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/) — Weijie Liu, Peng Zhou, Zhiruo Wang, et al. · 2020 - [FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/) — Esin Durmus, He He, Mona Diab · 2020 - [Few-shot Natural Language Generation for Task-Oriented Dialog](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/) — Baolin Peng, Chenguang Zhu, Chunyuan Li, et al. · 2020 - [Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network](https://md.research.elamur.ai/free/en/papers/hou-2020-few-shot-slot-tagging-collapsed/) — Yutai Hou, Wanxiang Che, Yongkui Lai, et al. · 2020 - [Fine-grained Fact Verification with Kernel Graph Attention Network](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/) — Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al. · 2020 - [Fine-grained Information Status Classification Using Discourse Context-Aware BERT](https://md.research.elamur.ai/free/en/papers/hou-2020-fine-grained-information-status-classification/) — Yufang Hou · 2020 - [From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers](https://md.research.elamur.ai/free/en/papers/lauscher-2020-zero-hero-limitations-zero-shot/) — Anne Lauscher, Vinit Ravishankar, Ivan Vulić, et al. · 2020 - [Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus](https://md.research.elamur.ai/free/en/papers/bentivogli-2020-gender-danger-evaluating-speech-translation/) — Luisa Bentivogli, Beatrice Savoldi, Matteo Negri, et al. · 2020 - [Generating Fact Checking Explanations](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/) — Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al. · 2020 - [Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) — Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al. · 2020 - [German's Next Language Model](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/) — Branden Chan, Stefan Schweter, Timo Möller · 2020 - [GLUECoS: An Evaluation Benchmark for Code-Switched NLP](https://md.research.elamur.ai/free/en/papers/khanuja-2020-gluecos-evaluation-benchmark-code-switched/) — Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan, et al. · 2020 - [Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://md.research.elamur.ai/free/en/papers/wang-2020-heterogeneous-graph-neural-networks-extractive/) — Danqing Wang, Pengfei Liu, Yining Zheng, et al. · 2020 - [HopeEDI: A Multilingual Hope Speech Detection Dataset for Equality, Diversity, and Inclusion](https://md.research.elamur.ai/free/en/papers/chakravarthi-2020-hopeedi-multilingual-hope-speech-detection/) — Bharathi Raja Chakravarthi · 2020 - [HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) — Yichen Jiang, Shikha Bordia, Zheng Zhong, et al. · 2020 - [How Can We Know What Language Models Know?](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/) — Zhengbao Jiang, Frank F. Xu, Jun Araki, et al. · 2020 - [How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence](https://md.research.elamur.ai/free/en/papers/zhong-2020-how-does-nlp-benefit-legal/) — Haoxi Zhong, Chaojun Xiao, Cunchao Tu, et al. · 2020 - [Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation](https://md.research.elamur.ai/free/en/papers/zhang-2020-improving-massively-multilingual-neural-machine/) — Biao Zhang, Philip Williams, Ivan Titov, et al. · 2020 - [IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/) — Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla, et al. · 2020 [← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/38/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [38](https://md.research.elamur.ai/free/en/shelves/nlp/page/38/) **39** [40](https://md.research.elamur.ai/free/en/shelves/nlp/page/40/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/40/)