---
title: "Greater Boston — works: 357 in our library, the most cited first"
description: "Works of Greater Boston: 357 in our library · page 1 of 4, the most cited first. Among them: SciPy 1.0 — Fundamental Algorithms for Scientific…"
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# Works of Greater Boston

357 · page 1 of 4 · the most cited first · [← Greater Boston](https://md.research.elamur.ai/free/en/agglomerations/greater-boston/)

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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. **[MIMIC-III, a freely accessible critical care database](https://md.research.elamur.ai/free/en/papers/johnson-2016-mimic-iii-freely-accessible-critical/) [Scientific Data](https://md.research.elamur.ai/free/en/venues/scientific-data/)**Alistair E. W. Johnson, Tom Pollard, Lu Shen, et al.*2016 · 8,544 citations*
3. [**Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models PLOS Digital Health**Tiffany H. Kung, Morgan Cheatham, Arielle Medenilla, et al.*2023 · 4,168 citations*](https://md.research.elamur.ai/free/en/papers/kung-2023-performance-chatgpt-usmle-potential-ai/)
4. **[MIMIC-IV, a freely accessible electronic health record dataset](https://md.research.elamur.ai/free/en/papers/johnson-2023-mimic-iv-freely-accessible-electronic/) [Scientific Data](https://md.research.elamur.ai/free/en/venues/scientific-data/)**Alistair E. W. Johnson, Lucas Bulgarelli, Lu Shen, et al.*2023 · 3,386 citations*
5. [**Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books arXiv:1506.06724**Yukun Zhu, Ryan Kiros, Richard Zemel, et al.*2015 · 3,051 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2015-aligning-books-movies-towards-story/)
6. **[OpenNMT: Open-Source Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,469 citations*
7. **[Statistical Significance Tests for Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/koehn-2004-statistical-significance-tests-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Philipp Koehn*2004 · 2,444 citations*
8. **[A Primer in BERTology: What We Know About How BERT Works](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,134 citations*
9. [**Centering: A Framework for Modeling the Local Coherence of Discourse**Barbara J. Grosz, Aravind K. Joshi, Scott Weinstein*1995 · 2,103 citations*](https://md.research.elamur.ai/free/en/papers/grosz-1995-centering-framework-modeling-local-coherence/)
10. [**Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings arXiv:1607.06520**Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al.*2016 · 2,050 citations*](https://md.research.elamur.ai/free/en/papers/bolukbasi-2016-man-computer-programmer-woman-homemaker/)
11. **[A Maximum-Entropy-Inspired Parser](https://md.research.elamur.ai/free/en/papers/charniak-2000-maximum-entropy-inspired-parser/) [Conference on Applied Natural Language Processing (ANLP)](https://md.research.elamur.ai/free/en/venues/anlp/)**Eugene Charniak*2000 · 2,050 citations*
12. **[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*
13. [**Head-Driven Statistical Models for Natural Language Parsing**Michael Collins*2003 · 2,001 citations*](https://md.research.elamur.ai/free/en/papers/collins-2003-head-driven-statistical-models-natural/)
14. **[Making Pre-trained Language Models Better Few-shot Learners](https://md.research.elamur.ai/free/en/papers/gao-2021-making-pre-trained-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Adam Fisch, Danqi Chen*2021 · 1,963 citations*
15. **[Character-Aware Neural Language Models](https://md.research.elamur.ai/free/en/papers/kim-2015-character-aware-neural-language-models/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yoon Kim, Yacine Jernite, David Sontag, et al.*2015 · 1,860 citations*
16. [**Towards Deep Learning Models Resistant to Adversarial Attacks arXiv:1706.06083**Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, et al.*2017 · 1,788 citations*](https://md.research.elamur.ai/free/en/papers/madry-2017-towards-deep-learning-models-resistant/)
17. [**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/)
18. [**Multitask Prompted Training Enables Zero-Shot Task Generalization arXiv:2110.08207**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,581 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
19. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*
20. **[ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks](https://md.research.elamur.ai/free/en/papers/gilardi-2023-chatgpt-outperforms-crowd-workers-text/) [Proceedings of the National Academy of Sciences](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-national-academy-of-sciences/)**Fabrizio Gilardi, Meysam Alizadeh, Maël Kubli*2023 · 1,533 citations*
21. **[GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,452 citations*
22. **[Sequence-Level Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yoon Kim, Alexander M. Rush*2016 · 1,445 citations*
23. **[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*
24. [**Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking**Eugene Charniak, Mark Johnson*2005 · 1,312 citations*](https://md.research.elamur.ai/free/en/papers/charniak-2005-coarse-fine-n-best-parsing/)
25. [**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/)
26. **[An Empirical Study of Smoothing Techniques for Language Modeling](https://md.research.elamur.ai/free/en/papers/chen-1996-empirical-study-smoothing-techniques-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Stanley F. Chen, Joshua Goodman*1996 · 1,217 citations*
27. **[StereoSet: Measuring stereotypical bias in pretrained language models](https://md.research.elamur.ai/free/en/papers/nadeem-2021-stereoset-measuring-stereotypical-bias-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moin Nadeem, Anna Bethke, Siva Reddy*2021 · 1,132 citations*
28. **[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*
29. **[Abstractive Sentence Summarization with Attentive Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/chopra-2016-abstractive-sentence-summarization-attentive-recurrent/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sumit Chopra, Michael Auli, Alexander M. Rush*2016 · 1,091 citations*
30. [**Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars arXiv:1207.1420**Luke S. Zettlemoyer, Michael Collins*2012 · 1,074 citations*](https://md.research.elamur.ai/free/en/papers/zettlemoyer-2012-learning-map-sentences-logical-form/)
31. [**CoNLL-2012 Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes**Sameer Pradhan, Alessandro Moschitti, Nianwen Xue, et al.*2012 · 1,066 citations*](https://md.research.elamur.ai/free/en/papers/pradhan-2012-conll-2012-shared-task-modeling/)
32. [**A Model-Theoretic Coreference Scoring Scheme**Marc Vilain, John Burger, John Aberdeen, et al.*1995 · 1,055 citations*](https://md.research.elamur.ai/free/en/papers/vilain-1995-model-theoretic-coreference-scoring-scheme/)
33. **[GPT Understands, Too](https://md.research.elamur.ai/free/en/papers/liu-2021-gpt-understands-too/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Xiao Liu, Yanan Zheng, Zhengxiao Du, et al.*2021 · 1,045 citations*
34. **[A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://md.research.elamur.ai/free/en/papers/cohan-2018-discourse-aware-attention-model-abstractive/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arman Cohan, Franck Dernoncourt, Doo Soon Kim, et al.*2018 · 1,022 citations*
35. **[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*
36. [**Discriminative Reranking for Natural Language Parsing**Michael Collins, Terry Koo*2000 · 990 citations*](https://md.research.elamur.ai/free/en/papers/collins-2000-discriminative-reranking-natural-language-parsing/)
37. **[Bottom-Up Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/gehrmann-2018-bottom-up-abstractive-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Gehrmann, Yuntian Deng, Alexander Rush*2018 · 944 citations*
38. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models arXiv:2304.01852 · Meta-Radiology (2023)100,017**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 938 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
39. **[Rationalizing Neural Predictions](https://md.research.elamur.ai/free/en/papers/lei-2016-rationalizing-neural-predictions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Lei, Regina Barzilay, Tommi Jaakkola*2016 · 935 citations*
40. **[Clause Restructuring for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/collins-2005-clause-restructuring-statistical-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Collins, Philipp Koehn, Ivona Kučerová*2005 · 919 citations*
41. **[Modeling Local Coherence: An Entity-Based Approach](https://md.research.elamur.ai/free/en/papers/barzilay-2008-modeling-local-coherence-entity-based/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Regina Barzilay, Mirella Lapata*2008 · 913 citations*
42. [**Extracting Training Data from Large Language Models arXiv:2012.07805**Nicholas Carlini, Florian Tramer, Eric Wallace, et al.*2020 · 911 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2020-extracting-training-data-large-language/)
43. **[TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP](https://md.research.elamur.ai/free/en/papers/morris-2020-textattack-framework-adversarial-attacks-data/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John X. Morris, Eli Lifland, Jin Yong Yoo, et al.*2020 · 858 citations*
44. **[Challenges in Data-to-Document Generation](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 850 citations*
45. [**Effective Self-Training for Parsing**David McClosky, Eugene Charniak, Mark Johnson*2006 · 847 citations*](https://md.research.elamur.ai/free/en/papers/mcclosky-2006-effective-self-training-parsing/)
46. **[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*
47. **[ERASER: A Benchmark to Evaluate Rationalized NLP Models](https://md.research.elamur.ai/free/en/papers/deyoung-2020-eraser-benchmark-evaluate-rationalized-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, et al.*2020 · 821 citations*
48. [**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/)
49. [**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/)
50. **[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*
51. [**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/)
52. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 695 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
53. **[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*
54. **[Simple Semi-supervised Dependency Parsing](https://md.research.elamur.ai/free/en/papers/koo-2008-simple-semi-supervised-dependency-parsing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terry Koo, Xavier Carreras, Michael Collins*2008 · 657 citations*
55. **[Discriminating Gender on Twitter](https://md.research.elamur.ai/free/en/papers/burger-2011-discriminating-gender-twitter/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John D. Burger, John Henderson, George Kim, et al.*2011 · 632 citations*
56. [**The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages**Jan Hajič, Massimiliano Ciaramita, Richard Johansson, et al.*2009 · 631 citations*](https://md.research.elamur.ai/free/en/papers/hajic-2009-conll-2009-shared-task-syntactic/)
57. **[Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 621 citations*
58. **[Object Hallucination in Image Captioning](https://md.research.elamur.ai/free/en/papers/rohrbach-2018-object-hallucination-image-captioning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, et al.*2018 · 619 citations*
59. **[A Critique and Improvement of an Evaluation Metric for Text Segmentation](https://md.research.elamur.ai/free/en/papers/pevzner-2002-critique-improvement-evaluation-metric-text/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lev Pevzner, Marti A. Hearst*2002 · 595 citations*
60. [**How Powerful are Graph Neural Networks? arXiv:1810.00826**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 594 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
61. [**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/)
62. **[ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/hartvigsen-2022-toxigen-large-scale-machine-generated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.*2022 · 571 citations*
63. [**Incremental Parsing with the Perceptron Algorithm**Michael Collins, Brian Roark*2004 · 568 citations*](https://md.research.elamur.ai/free/en/papers/collins-2004-incremental-parsing-perceptron-algorithm/)
64. [**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/)
65. [**Improving Factuality and Reasoning in Language Models through Multiagent Debate arXiv:2305.14325**Yilun Du, Shuang Li, Antonio Torralba, et al.*2023 · 565 citations*](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/)
66. **[Finding Parts in Very Large Corpora](https://md.research.elamur.ai/free/en/papers/berland-1999-finding-parts-very-large-corpora/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Matthew Berland, Eugene Charniak*1999 · 561 citations*
67. **[Sentence Fusion for Multidocument News Summarization](https://md.research.elamur.ai/free/en/papers/barzilay-2005-sentence-fusion-multidocument-news-summarization/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Regina Barzilay, Kathleen R. McKeown*2005 · 549 citations*
68. [**What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams arXiv:2009.13081**Di Jin, Eileen Pan, Nassim Oufattole, et al.*2020 · 546 citations*](https://md.research.elamur.ai/free/en/papers/jin-2020-disease-this-patient-have-large/)
69. **[Edinburgh System Description for the 2005 IWSLT Speech Translation Evaluation](https://md.research.elamur.ai/free/en/papers/koehn-2005-edinburgh-system-description-2005-iwslt/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Philipp Koehn, Amittai Axelrod, Alexandra Birch Mayne, et al.*2005 · 545 citations*
70. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
71. [**Learning to Solve Arithmetic Word Problems with Verb Categorization**Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, et al.*2014 · 513 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2014-learning-solve-arithmetic-word-problems/)
72. **[Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/lee-2016-sequential-short-text-classification-recurrent/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ji Young Lee, Franck Dernoncourt*2016 · 512 citations*
73. **[Benchmarking Aggression Identification in Social Media](https://md.research.elamur.ai/free/en/papers/kumar-2018-benchmarking-aggression-identification-social-media/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Ritesh Kumar, Atul Kr. Ojha, Shervin Malmasi, et al.*2018 · 510 citations*
74. **[Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses](https://md.research.elamur.ai/free/en/papers/lowe-2017-towards-automatic-turing-test-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryan Lowe, Michael Noseworthy, Iulian V. Serban, et al.*2017 · 495 citations*
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