---
title: "Arts and Humanities — papers, page 2"
description: "Arts and Humanities: 7,418 papers of the Elamur Research library · page 2 of 75 · 26–125, the most cited first — our summary of each, its ideas…"
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---
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# 🎭 Arts and Humanities

7,418 papers · page 2 of 75 · 26–125 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Languages and linguistics, history, philosophy, literature, religion, music and the arts.

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) [1](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) **2** [3](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/page/3/) … [75](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/page/75/) [next →](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/page/3/)

26. [**ROUGE: A Package for Automatic Evaluation of Summaries**Chin-Yew Lin*2004 · 5,641 citations*](https://md.research.elamur.ai/free/en/papers/lin-2004-rouge-package-automatic-evaluation-summaries/)
27. [**METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments**Satanjeev Banerjee, Alon Lavie*2005 · 5,483 citations*](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/)
28. [**Hierarchical Attention Networks for Document Classification**Zichao Yang, Diyi Yang, Chris Dyer, et al.*2016 · 5,409 citations*](https://md.research.elamur.ai/free/en/papers/yang-2016-hierarchical-attention-networks-document-classification/)
29. [**Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing**Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.*2021 · 5,375 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/)
30. [**Dense Passage Retrieval for Open-Domain Question Answering**Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al.*2020 · 5,370 citations*](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/)
31. [**Explanation in Artificial Intelligence: Insights from the Social Sciences**Tim Miller*2017 · 5,362 citations*](https://md.research.elamur.ai/free/en/papers/miller-2017-explanation-artificial-intelligence-insights-social/)
32. [**WaveNet: A Generative Model for Raw Audio**Aaron van den Oord, Sander Dieleman, Heiga Zen, et al.*2016 · 5,167 citations*](https://md.research.elamur.ai/free/en/papers/oord-2016-wavenet-generative-model-raw-audio/)
33. [**Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks**Nils Reimers, Iryna Gurevych*2019 · 4,838 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2019-sentence-bert-sentence-embeddings-siamese/)
34. [**Character-level Convolutional Networks for Text Classification**Xiang Zhang, Junbo Zhao, Yann LeCun*2015 · 4,753 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2015-character-level-convolutional-networks-text/)
35. [**DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning**DeepSeek-AI, Daya Guo, Dejian Yang, et al.*2025 · 4,593 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-r1-incentivizing-reasoning-capability/)
36. [**Rhetorical Structure Theory: Toward a functional theory of text organization**William C. Mann, Sandra A. Thompson*1988 · 4,547 citations*](https://md.research.elamur.ai/free/en/papers/mann-1988-rhetorical-structure-theory-functional/)
37. [**Large Language Models Encode Clinical Knowledge**Karan Singhal, Shekoofeh Azizi, Tao Tu, et al.*2022 · 4,464 citations*](https://md.research.elamur.ai/free/en/papers/singhal-2022-large-language-models-encode-clinical/)
38. [**SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing**Taku Kudo, John Richardson*2018 · 4,461 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2018-sentencepiece-simple-language-independent-subword/)
39. [**Word Association Norms, Mutual Information, and Lexicography**Kenneth Ward Church, Patrick Hanks*1990 · 4,363 citations*](https://md.research.elamur.ai/free/en/papers/church-1990-word-association-norms-mutual-information/)
40. [**Learning Word Vectors for Sentiment Analysis**Andrew L. Maas, Raymond E. Daly, Peter T. Pham, et al.*2011 · 4,272 citations*](https://md.research.elamur.ai/free/en/papers/maas-2011-learning-word-vectors-sentiment-analysis/)
41. [**The Cambridge Grammar of the English Language**Rodney Huddleston, Geoffrey K. Pullum*2002 · 4,249 citations*](https://md.research.elamur.ai/free/en/papers/huddleston-2002-cambridge-grammar-english-language/)
42. [**A Call for Clarity in Reporting BLEU Scores**Matt Post*2018 · 4,130 citations*](https://md.research.elamur.ai/free/en/papers/post-2018-call-clarity-reporting-bleu-scores/)
43. [**Energy and Policy Considerations for Deep Learning in NLP**Emma Strubell, Ananya Ganesh, Andrew McCallum*2019 · 4,049 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2019-energy-policy-considerations-deep-learning/)
44. [**Natural Questions: A Benchmark for Question Answering Research**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,031 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/)
45. [**Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis**Theresa Wilson, Janyce Wiebe, Paul Hoffmann*2005 · 3,979 citations*](https://md.research.elamur.ai/free/en/papers/wilson-2005-recognizing-contextual-polarity-phrase-level/)
46. [**Accurate Unlexicalized Parsing**Dan Klein, Christopher D. Manning*2003 · 3,942 citations*](https://md.research.elamur.ai/free/en/papers/klein-2003-accurate-unlexicalized-parsing/)
47. [**fairseq: A Fast, Extensible Toolkit for Sequence Modeling**Myle Ott, Sergey Edunov, Alexei Baevski, et al.*2019 · 3,941 citations*](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/)
48. [**SimCSE: Simple Contrastive Learning of Sentence Embeddings**Tianyu Gao, Xingcheng Yao, Danqi Chen*2021 · 3,921 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-simcse-simple-contrastive-learning-sentence/)
49. [**A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts**Bo Pang, Lillian Lee*2004 · 3,842 citations*](https://md.research.elamur.ai/free/en/papers/pang-2004-sentimental-education-sentiment-analysis-subjectivity/)
50. [**A Study of Translation Edit Rate with Targeted Human Annotation**Matthew Snover, Bonnie Dorr, Rich Schwartz, et al.*2006 · 3,824 citations*](https://md.research.elamur.ai/free/en/papers/snover-2006-study-translation-edit-rate-targeted/)
51. [**Teaching Machines to Read and Comprehend**Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, et al.*2015 · 3,806 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2015-teaching-machines-read-comprehend/)
52. [**SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition**Daniel S. Park, William Chan, Yu Zhang, et al.*2019 · 3,802 citations*](https://md.research.elamur.ai/free/en/papers/park-2019-specaugment-simple-data-augmentation-method/)
53. [**Bidirectional LSTM-CRF Models for Sequence Tagging**Zhiheng Huang, Wei Xu, Kai Yu*2015 · 3,802 citations*](https://md.research.elamur.ai/free/en/papers/huang-2015-bidirectional-lstm-crf-models-sequence/)
54. [**Large language models are zero-shot reasoners**Takeshi Kojima, Shixiang Shane Gu, Machel Reid, et al.*2022 · 3,780 citations*](https://md.research.elamur.ai/free/en/papers/kojima-2022-large-language-models-zero-shot/)
55. [**XLNet: Generalized Autoregressive Pretraining for Language Understanding**Zhilin Yang, Zihang Dai, Yiming Yang, et al.*2019 · 3,740 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-xlnet-generalized-autoregressive-pretraining-language/)
56. [**Training Verifiers to Solve Math Word Problems**Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, et al.*2021 · 3,675 citations*](https://md.research.elamur.ai/free/en/papers/cobbe-2021-training-verifiers-solve-math-word/)
57. [**A Survey on Evaluation of Large Language Models**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,640 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/)
58. [**A Maximum Entropy Approach to Natural Language Processing**Adam L. Berger, Stephen A. Della Pietra, Vincent J. Della Pietra*1996 · 3,633 citations*](https://md.research.elamur.ai/free/en/papers/berger-1996-maximum-entropy-approach-natural-language/)
59. [**Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling**Jenny Rose Finkel, Trond Grenager, Christopher Manning*2005 · 3,618 citations*](https://md.research.elamur.ai/free/en/papers/finkel-2005-incorporating-non-local-information-into/)
60. [**Categorical Reparameterization with Gumbel-Softmax**Eric Jang, Shixiang Gu, Ben Poole*2016 · 3,571 citations*](https://md.research.elamur.ai/free/en/papers/jang-2016-categorical-reparameterization-gumbel-softmax/)
61. [**Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network**Kristina Toutanova, Dan Klein, Christopher D. Manning, et al.*2003 · 3,559 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2003-feature-rich-part-speech-tagging/)
62. [**Lexicon-Based Methods for Sentiment Analysis**Maite Taboada, Julian Brooke, Milan Tofiloski, et al.*2011 · 3,556 citations*](https://md.research.elamur.ai/free/en/papers/taboada-2011-lexicon-based-methods-sentiment-analysis/)
63. [**SciBERT: A Pretrained Language Model for Scientific Text**Iz Beltagy, Kyle Lo, Arman Cohan*2019 · 3,548 citations*](https://md.research.elamur.ai/free/en/papers/beltagy-2019-scibert-pretrained-language-model-scientific/)
64. [**The Berkeley FrameNet Project**Collin F. Baker, Charles J. Fillmore, John B. Lowe*1998 · 3,544 citations*](https://md.research.elamur.ai/free/en/papers/baker-1998-berkeley-framenet/)
65. [**Measuring Massive Multitask Language Understanding**Dan Hendrycks, Collin Burns, Steven Basart, et al.*2020 · 3,489 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-measuring-massive-multitask-language-understanding/)
66. [**HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering**Zhilin Yang, Peng Qi, Saizheng Zhang, et al.*2018 · 3,489 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-hotpotqa-dataset-diverse-explainable-multi/)
67. [**Linguistic Regularities in Continuous Space Word Representations**Tomas Mikolov, Wen-tau Yih, Geoffrey Zweig*2013 · 3,482 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-linguistic-regularities-continuous-space-word/)
68. [**HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units**Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, et al.*2021 · 3,441 citations*](https://md.research.elamur.ai/free/en/papers/hsu-2021-hubert-self-supervised-speech-representation/)
69. [**Conformer: Convolution-augmented Transformer for Speech Recognition**Anmol Gulati, James Qin, Chung-Cheng Chiu, et al.*2020 · 3,433 citations*](https://md.research.elamur.ai/free/en/papers/gulati-2020-conformer-convolution-augmented-transformer-speech/)
70. [**Using Information Content to Evaluate Semantic Similarity in a Taxonomy**Philip Resnik*1995 · 3,419 citations*](https://md.research.elamur.ai/free/en/papers/resnik-1995-information-content-evaluate-semantic-similarity/)
71. [**Know What You Don't Know: Unanswerable Questions for SQuAD**Pranav Rajpurkar, Robin Jia, Percy Liang*2018 · 3,360 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2018-know-what-you-don-t/)
72. [**Qwen3 Technical Report**An Yang, Anfeng Li, Baosong Yang, et al.*2025 · 3,276 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen3-technical-report/)
73. [**Verb Semantics and Lexical Selection**Zhibiao Wu, Martha Palmer*1994 · 3,276 citations*](https://md.research.elamur.ai/free/en/papers/wu-1994-verb-semantics-lexical-selection/)
74. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
75. [**The Proposition Bank: An Annotated Corpus of Semantic Roles**Martha Palmer, Daniel Gildea, Paul Kingsbury*2005 · 3,208 citations*](https://md.research.elamur.ai/free/en/papers/palmer-2005-proposition-bank-annotated-corpus-semantic/)
76. [**TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension**Mandar Joshi, Eunsol Choi, Daniel Weld, et al.*2017 · 3,204 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2017-triviaqa-large-scale-distantly-supervised/)
77. [**SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining**Stefano Baccianella, Andrea Esuli, Fabrizio Sebastiani*2010 · 3,068 citations*](https://md.research.elamur.ai/free/en/papers/baccianella-2010-sentiwordnet-3-0-enhanced-lexical/)
78. [**Accurate Methods for the Statistics of Surprise and Coincidence**Ted Dunning*1993 · 3,060 citations*](https://md.research.elamur.ai/free/en/papers/dunning-1993-accurate-methods-statistics-surprise-coincidence/)
79. [**On the Opportunities and Risks of Foundation Models**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,044 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
80. [**Self-Consistency Improves Chain of Thought Reasoning in Language Models**Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.*2022 · 3,035 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-self-consistency-improves-chain-thought/)
81. [**Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books**Yukun Zhu, Ryan Kiros, Richard Zemel, et al.*2015 · 3,030 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2015-aligning-books-movies-towards-story/)
82. [**Building a Large Annotated Corpus of English: The Penn Treebank**Mitchell P. Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz*1993 · 3,006 citations*](https://md.research.elamur.ai/free/en/papers/marcus-1993-building-large-annotated-corpus-english/)
83. [**Convolutional Sequence to Sequence Learning**Jonas Gehring, Michael Auli, David Grangier, et al.*2017 · 2,983 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-sequence-sequence-learning/)
84. [**Language Models as Knowledge Bases?**Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.*2019 · 2,977 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2019-language-models-as-knowledge-bases/)
85. [**CodeBERT: A Pre-Trained Model for Programming and Natural Languages**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,954 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)
86. [**Gemini: A Family of Highly Capable Multimodal Models**Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.*2023 · 2,951 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2023-gemini-family-highly-capable-multimodal/)
87. [**A Diversity-Promoting Objective Function for Neural Conversation Models**Jiwei Li, Michel Galley, Chris Brockett, et al.*2016 · 2,925 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/)
88. [**Attention, Intentions, and the Structure of Discourse**Barbara J. Grosz, Candace L. Sidner*1986 · 2,923 citations*](https://md.research.elamur.ai/free/en/papers/grosz-1986-attention-intentions-structure-discourse/)
89. [**Generating Typed Dependency Parses from Phrase Structure Parses**Marie-Catherine de Marneffe, Bill MacCartney, Christopher D. Manning*2006 · 2,886 citations*](https://md.research.elamur.ai/free/en/papers/marneffe-2006-generating-typed-dependency-parses-phrase/)
90. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
91. [**Unsupervised Word Sense Disambiguation Rivaling Supervised Methods**David Yarowsky*1995 · 2,840 citations*](https://md.research.elamur.ai/free/en/papers/yarowsky-1995-unsupervised-word-sense-disambiguation-rivaling/)
92. [**Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews**Peter Turney*2002 · 2,826 citations*](https://md.research.elamur.ai/free/en/papers/turney-2002-thumbs-up-or-thumbs-down/)
93. [**Self-Attention with Relative Position Representations**Peter Shaw, Jakob Uszkoreit, Ashish Vaswani*2018 · 2,811 citations*](https://md.research.elamur.ai/free/en/papers/shaw-2018-self-attention-relative-position-representations/)
94. [**RCV1: A New Benchmark Collection for Text Categorization Research**David D. Lewis, Yiming Yang, Tony G. Rose, et al.*2004 · 2,742 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2004-rcv1-benchmark-collection-text-categorization/)
95. [**Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales**Bo Pang, Lillian Lee*2005 · 2,722 citations*](https://md.research.elamur.ai/free/en/papers/pang-2005-seeing-stars-exploiting-class-relationships/)
96. [**SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining**Andrea Esuli, Fabrizio Sebastiani*2006 · 2,719 citations*](https://md.research.elamur.ai/free/en/papers/esuli-2006-sentiwordnet-publicly-available-lexical-resource/)
97. [**LXMERT: Learning Cross-Modality Encoder Representations from Transformers**Hao Tan, Mohit Bansal*2019 · 2,714 citations*](https://md.research.elamur.ai/free/en/papers/tan-2019-lxmert-learning-cross-modality-encoder/)
98. [**Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing**Yu Gu; Robert Tinn; Hao Cheng; Michael Lucas; Naoto Usuyama; Xiaodong Liu; Tristan Naumann; Jianfeng Gao;, Hoifung Poon*2020 · 2,636 citations*](https://md.research.elamur.ai/free/en/papers/gu-2020-domain-specific-language-model-pretraining/)
99. [**Attention-based LSTM for Aspect-level Sentiment Classification**Yequan Wang, Minlie Huang, Xiaoyan Zhu, et al.*2016 · 2,609 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-attention-based-lstm-aspect-level/)
100. [**SpanBERT: Improving Pre-training by Representing and Predicting Spans**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,580 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/)
101. [**Lost in the Middle: How Language Models Use Long Contexts**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,540 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/)
102. [**Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms**Michael Collins*2002 · 2,510 citations*](https://md.research.elamur.ai/free/en/papers/collins-2002-discriminative-training-methods-hidden-markov/)
103. [**Dynamic Topic Models**David M. Blei, John D. Lafferty*2006 · 2,508 citations*](https://md.research.elamur.ai/free/en/papers/blei-2006-dynamic-topic-models/)
104. [**Robust Speech Recognition via Large-Scale Weak Supervision**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,497 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
105. [**Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Qingyang Wu, et al.*2023 · 2,487 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-visual-instruction-tuning/)
106. [**Assessing Agreement on Classification Tasks: The Kappa Statistic**Jean Carletta*1996 · 2,462 citations*](https://md.research.elamur.ai/free/en/papers/carletta-1996-assessing-agreement-classification-tasks-kappa/)
107. [**OpenNMT: Open-Source Toolkit for Neural Machine Translation**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,460 citations*](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/)
108. [**Statistical Significance Tests for Machine Translation Evaluation**Philipp Koehn*2004 · 2,444 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2004-statistical-significance-tests-machine-translation/)
109. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
110. [**SemEval-2014 Task 4: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, John Pavlopoulos, et al.*2014 · 2,405 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2014-semeval-2014-task-4-aspect/)
111. [**Meteor Universal: Language Specific Translation Evaluation for Any Target Language**Michael Denkowski, Alon Lavie*2014 · 2,392 citations*](https://md.research.elamur.ai/free/en/papers/denkowski-2014-meteor-universal-language-specific-translation/)
112. [**Sparks of Artificial General Intelligence: Early experiments with GPT-4**Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.*2023 · 2,389 citations*](https://md.research.elamur.ai/free/en/papers/bubeck-2023-sparks-artificial-general-intelligence-early/)
113. [**Recurrent Neural Network Regularization**Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals*2014 · 2,379 citations*](https://md.research.elamur.ai/free/en/papers/zaremba-2014-recurrent-neural-network-regularization/)
114. [**Exploring the Space of Topic Coherence Measures**Michael Röder, Andreas Both, Alexander Hinneburg*2015 · 2,368 citations*](https://md.research.elamur.ai/free/en/papers/roder-2015-exploring-space-topic-coherence-measures/)
115. [**Generating Sentences from a Continuous Space**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/)
116. [**Self-critical Sequence Training for Image Captioning**Steven J. Rennie, Etienne Marcheret, Youssef Mroueh, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/rennie-2016-self-critical-sequence-training-image/)
117. [**Stanza: A Python Natural Language Processing Toolkit for Many Human Languages**Peng Qi, Yuhao Zhang, Yuhui Zhang, et al.*2020 · 2,347 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-stanza-python-natural-language-processing/)
118. [**Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification**John Blitzer, Mark Dredze, Fernando Pereira*2007 · 2,329 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2007-biographies-bollywood-boom-boxes-blenders/)
119. [**Measuring Mathematical Problem Solving With the MATH Dataset**Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.*2021 · 2,318 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-mathematical-problem-solving-math/)
120. [**Deep Speech 2: End-to-End Speech Recognition in English and Mandarin**Dario Amodei, Rishita Anubhai, Eric Battenberg, et al.*2015 · 2,302 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2015-deep-speech-2-end-end/)
121. [**A Fast and Accurate Dependency Parser using Neural Networks**Danqi Chen, Christopher Manning*2014 · 2,301 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-fast-accurate-dependency-parser-neural/)
122. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
123. [**A Survey on Large Language Model based Autonomous Agents**Lei Wang, Chen Ma, Xueyang Feng, et al.*2023 · 2,263 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-large-language-model-based/)
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