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title: "Natural language processing — papers, page 34"
description: "Natural language processing: 2421 papers of the Elamur Research library · page 34 of 97 — our summary of each, its ideas, references and who cites it."
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# 💬 Natural language processing

2421 papers · page 34 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.

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- [Referenceless Parsing-Based Evaluation of AMR-to-English Generation](https://md.research.elamur.ai/free/en/papers/manning-2021-referenceless-parsing-based-evaluation-amr/) — Emma Manning, Nathan Schneider · 2021
- [Resolving Prepositional Phrase Attachment Ambiguities with Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/aclbulk-2021-ratnaparkhi-resolving-prepositional-phrase-attachment-ambiguities/) — Adwait Ratnaparkhi, Atul Kumar · 2021
- [RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/) — Yingqi Qu, Yuchen Ding, Jing Liu, et al. · 2021
- [RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking](https://md.research.elamur.ai/free/en/papers/ren-2021-rocketqav2-joint-training-method-dense/) — Ruiyang Ren, Yingqi Qu, Jing Liu, et al. · 2021
- [Self-Alignment Pretraining for Biomedical Entity Representations](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/) — Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al. · 2021
- [Self-Guided Contrastive Learning for BERT Sentence Representations](https://md.research.elamur.ai/free/en/papers/kim-2021-self-guided-contrastive-learning-bert/) — Taeuk Kim, Kang Min Yoo, Sang-goo Lee · 2021
- [SemEval-2021 Task 1: Lexical Complexity Prediction](https://md.research.elamur.ai/free/en/papers/shardlow-2021-semeval-2021-task-1-lexical/) — Matthew Shardlow, Richard Evans, Gustavo Henrique Paetzold, et al. · 2021
- [SemEval-2021 Task 5: Toxic Spans Detection](https://md.research.elamur.ai/free/en/papers/pavlopoulos-2021-semeval-2021-task-5-toxic/) — John Pavlopoulos, Jeffrey Sorensen, Léo Laugier, et al. · 2021
- [SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2021-simcls-simple-framework-contrastive-learning/) — Yixin Liu, Pengfei Liu · 2021
- [Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) — Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al. · 2021
- [Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages](https://md.research.elamur.ai/free/en/papers/ogueji-2021-small-data-no-problem-exploring/) — Kelechi Ogueji, Yuxin Zhu, Jimmy Lin · 2021
- [Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) — Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al. · 2021
- [Sparse, Dense, and Attentional Representations for Text Retrieval](https://md.research.elamur.ai/free/en/papers/luan-2021-sparse-dense-attentional-representations-text/) — Yi Luan, Jacob Eisenstein, Kristina Toutanova, et al. · 2021
- [StereoSet: Measuring stereotypical bias in pretrained language models](https://md.research.elamur.ai/free/en/papers/nadeem-2021-stereoset-measuring-stereotypical-bias-pretrained/) — Moin Nadeem, Anna Bethke, Siva Reddy · 2021
- [Structure-Grounded Pretraining for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) — Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al. · 2021
- [Supervised and Unsupervised Neural Approaches to Text Readability](https://md.research.elamur.ai/free/en/papers/martinc-2021-supervised-unsupervised-neural-approaches-text/) — Matej Martinc, Senja Pollak, Marko Robnik-Šikonja · 2021
- [Surface Form Competition: Why the Highest Probability Answer Isn't Always Right](https://md.research.elamur.ai/free/en/papers/holtzman-2021-surface-form-competition-why-highest/) — Ari Holtzman, Peter West, Vered Shwartz, et al. · 2021
- [Sustainable Modular Debiasing of Language Models](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/) — Anne Lauscher, Tobias Lueken, Goran Glavaš · 2021
- [Template-Based Named Entity Recognition Using BART](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/) — Leyang Cui, Yu Wu, Jian Liu, et al. · 2021
- [Text Generation from Discourse Representation Structures](https://md.research.elamur.ai/free/en/papers/liu-2021-text-generation-discourse-representation-structures/) — Jiangming Liu, Shay B. Cohen, Mirella Lapata · 2021
- [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/) — Yaojie Lu, Hongyu Lin, Jin Xu, et al. · 2021
- [The (Un)Suitability of Automatic Evaluation Metrics for Text Simplification](https://md.research.elamur.ai/free/en/papers/manchego-2021-un-suitability-automatic-evaluation-metrics/) — Fernando Alva-Manchego, Carolina Scarton, Lucia Specia · 2021
- [The Curious Case of Hallucinations in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/raunak-2021-curious-case-hallucinations-neural-machine/) — Vikas Raunak, Arul Menezes, Marcin Junczys-Dowmunt · 2021
- [The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task](https://md.research.elamur.ai/free/en/papers/aly-2021-fact-extraction-verification-over-unstructured/) — Rami Aly, Zhijiang Guo, Michael Sejr Schlichtkrull, et al. · 2021
- [The Importance of Modeling Social Factors of Language: Theory and Practice](https://md.research.elamur.ai/free/en/papers/hovy-2021-importance-modeling-social-factors-language/) — Dirk Hovy, Diyi Yang · 2021

[← prev](https://md.research.elamur.ai/free/en/shelves/nlp/page/33/) [1](https://md.research.elamur.ai/free/en/shelves/nlp/) … [33](https://md.research.elamur.ai/free/en/shelves/nlp/page/33/) **34** [35](https://md.research.elamur.ai/free/en/shelves/nlp/page/35/) … [97](https://md.research.elamur.ai/free/en/shelves/nlp/page/97/) [next →](https://md.research.elamur.ai/free/en/shelves/nlp/page/35/)