---
title: "Greater Boston — works of 2019: 40 papers, the most cited first"
description: "40 works of Greater Boston from 2019 in our library, the most cited first. Among them: SciPy 1.0 — Fundamental Algorithms for Scientific…"
canonical: "https://research.elamur.ai/free/en/agglomerations/greater-boston/year/2019/"
---
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# Works of Greater Boston from 2019

40 works · the most cited first · [← Greater Boston](https://md.research.elamur.ai/free/en/agglomerations/greater-boston/)

1. [**SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python arXiv:1907.10121 (Nature Methods 17, 261 (2020))**Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, et al.*2019 · 38,317 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/)
2. **[BERT Rediscovers the Classical NLP Pipeline](https://md.research.elamur.ai/free/en/papers/tenney-2019-bert-rediscovers-classical-nlp-pipeline/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ian Tenney, Dipanjan Das, Ellie Pavlick*2019 · 2,002 citations*
3. [**Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference**R. Thomas McCoy, Ellie Pavlick, Tal Linzen*2019 · 1,635 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)
4. **[Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment](https://md.research.elamur.ai/free/en/papers/jin-2019-bert-really-robust-strong-baseline/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Di Jin, Zhijing Jin, Joey Tianyi Zhou, et al.*2019 · 1,326 citations*
5. [**Publicly Available Clinical BERT Embeddings arXiv:1904.03323**Emily Alsentzer, John R. Murphy, Willie Boag, et al.*2019 · 1,226 citations*](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/)
6. **[Predicting the Type and Target of Offensive Posts in Social Media](https://md.research.elamur.ai/free/en/papers/zampieri-2019-predicting-type-target-offensive-posts/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Marcos Zampieri, Shervin Malmasi, Preslav Nakov, et al.*2019 · 1,118 citations*
7. **[Linguistic Knowledge and Transferability of Contextual Representations](https://md.research.elamur.ai/free/en/papers/liu-2019-linguistic-knowledge-transferability-contextual-representations/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nelson F. Liu, Matt Gardner, Yonatan Belinkov, et al.*2019 · 1,015 citations*
8. **[Findings of the 2019 Conference on Machine Translation (WMT19)](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al.*2019 · 841 citations*
9. [**ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission arXiv:1904.05342**Kexin Huang, Jaan Altosaar, Rajesh Ranganath*2019 · 798 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/)
10. [**Revealing the Dark Secrets of BERT arXiv:1908.08593**Olga Kovaleva, Alexey Romanov, Anna Rogers, et al.*2019 · 745 citations*](https://md.research.elamur.ai/free/en/papers/kovaleva-2019-revealing-dark-secrets-bert/)
11. **[Analysis Methods in Neural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yonatan Belinkov, James Glass*2019 · 737 citations*
12. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 728 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
13. **[GLTR: Statistical Detection and Visualization of Generated Text](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush*2019 · 693 citations*
14. [**What do you learn from context? Probing for sentence structure in contextualized word representations arXiv:1905.06316**Ian Tenney, Patrick Xia, Berlin Chen, et al.*2019 · 588 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-learn-context-probing-sentence-structure/)
15. [**Plug and Play Language Models: A Simple Approach to Controlled Text Generation arXiv:1912.02164**Sumanth Dathathri, Andrea Madotto, Janice Lan, et al.*2019 · 567 citations*](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/)
16. [**Inherent Disagreements in Human Textual Inferences**Ellie Pavlick, Tom Kwiatkowski*2019 · 451 citations*](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/)
17. [**Analyzing the Structure of Attention in a Transformer Language Model arXiv:1906.04284**Jesse Vig, Yonatan Belinkov*2019 · 432 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/)
18. **[Commonsense Knowledge Mining from Pretrained Models](https://md.research.elamur.ai/free/en/papers/davison-2019-commonsense-knowledge-mining-pretrained-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joe Davison, Joshua Feldman, Alexander Rush*2019 · 413 citations*
19. **[Fine-Grained Analysis of Propaganda in News Articles](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al.*2019 · 379 citations*
20. **[MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension](https://md.research.elamur.ai/free/en/papers/fisch-2019-mrqa-2019-shared-task-evaluating/) [Workshop on Machine Reading for Question Answering](https://md.research.elamur.ai/free/en/venues/mrqa/)**Adam Fisch, Alon Talmor, Robin Jia, et al.*2019 · 375 citations*
21. **[Towards Debiasing Fact Verification Models](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations*
22. **[Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Ori Ram, Regina Barzilay, et al.*2019 · 295 citations*
23. **[Neural language models as psycholinguistic subjects: Representations of syntactic state](https://md.research.elamur.ai/free/en/papers/futrell-2019-neural-language-models-as-psycholinguistic/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2019 · 291 citations*
24. **[BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://md.research.elamur.ai/free/en/papers/sharma-2019-bigpatent-large-scale-dataset-abstractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eva Sharma, Chen Li, Lu Wang*2019 · 235 citations*
25. **[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/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Edoardo Maria Ponti, Helen O'Horan, Yevgeni Berzak, et al.*2019 · 217 citations*
26. **[Compound Probabilistic Context-Free Grammars for Grammar Induction](https://md.research.elamur.ai/free/en/papers/kim-2019-compound-probabilistic-context-free-grammars/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoon Kim, Chris Dyer, Alexander Rush*2019 · 196 citations*
27. **[Probing What Different NLP Tasks Teach Machines about Function Word Comprehension](https://md.research.elamur.ai/free/en/papers/kim-2019-probing-what-different-nlp-tasks/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Najoung Kim, Roma Patel, Adam Poliak, et al.*2019 · 161 citations*
28. **[Inferring Which Medical Treatments Work from Reports of Clinical Trials](https://md.research.elamur.ai/free/en/papers/lehman-2019-inferring-which-medical-treatments-work/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Eric Lehman, Jay DeYoung, Regina Barzilay, et al.*2019 · 159 citations*
29. **[Evaluating Style Transfer for Text](https://md.research.elamur.ai/free/en/papers/mir-2019-evaluating-style-transfer-text/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Remi Mir, Bjarke Felbo, Nick Obradovich, et al.*2019 · 155 citations*
30. **[Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing](https://md.research.elamur.ai/free/en/papers/wang-2019-cross-lingual-bert-transformation-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxuan Wang, Wanxiang Che, Jiang Guo, et al.*2019 · 153 citations*
31. **[Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-don-t-take-premise-granted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.*2019 · 121 citations*
32. **[Argument Generation with Retrieval, Planning, and Realization](https://md.research.elamur.ai/free/en/papers/hua-2019-argument-generation-retrieval-planning-realization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Hua, Zhe Hu, Lu Wang*2019 · 113 citations*
33. **[On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-adversarial-removal-hypothesis-only-bias/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.*2019 · 95 citations*
34. [**Pragmatically Informative Text Generation**Sheng Shen, Daniel Fried, Jacob Andreas, et al.*2019 · 78 citations*](https://md.research.elamur.ai/free/en/papers/shen-2019-pragmatically-informative-text-generation/)
35. [**ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets arXiv:1906.01830**Ramy Baly, Alaa Khaddaj, Hazem Hajj, et al.*2019 · 61 citations*](https://md.research.elamur.ai/free/en/papers/baly-2019-arsentd-lev-multi-topic-corpus/)
36. [**How well do NLI models capture verb veridicality?**Alexis Ross, Ellie Pavlick*2019 · 61 citations*](https://md.research.elamur.ai/free/en/papers/ross-2019-how-well-do-nli-models/)
37. [**Neural Decipherment via Minimum-Cost Flow: From Ugaritic to Linear B**Jiaming Luo, Yuan Cao, Regina Barzilay*2019 · 43 citations*](https://md.research.elamur.ai/free/en/papers/luo-2019-neural-decipherment-minimum-cost-flow/)
38. [**VerbNet Representations: Subevent Semantics for Transfer Verbs**Susan Windisch Brown, Julia Bonn, James Gung, et al.*2019 · 27 citations*](https://md.research.elamur.ai/free/en/papers/brown-2019-verbnet-representations-subevent-semantics-transfer/)
39. **[Cross-document coreference: An approach to capturing coreference without context](https://md.research.elamur.ai/free/en/papers/bettner-2019-cross-document-coreference-approach-capturing/) [International Workshop on Health Text Mining and Information Analysis (LOUHI)](https://md.research.elamur.ai/free/en/venues/international-workshop-on-health-text-mining-and-information-analysis-louhi/)**Kristin Wright-Bettner, Martha Palmer, Guergana Savova, et al.*2019 · 15 citations*
40. [**DARTS: Dialectal Arabic Transcription System arXiv:1909.12163**Sameer Khurana, Ahmed Ali, James Glass*2019 · 7 citations*](https://md.research.elamur.ai/free/en/papers/khurana-2019-darts-dialectal-arabic-transcription-system/)
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