---
title: "Arts and Humanities — papers, page 3"
description: "Arts and Humanities: 7,418 papers of the Elamur Research library · page 3 of 75 · 126–225, the most cited first — our summary of each, its ideas…"
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# 🎭 Arts and Humanities

7,418 papers · page 3 of 75 · 126–225 · 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/page/2/) [1](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) [2](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/page/2/) **3** [4](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/page/4/) … [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/4/)

126. [**ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks**Jiasen Lu, Dhruv Batra, Devi Parikh, et al.*2019 · 2,217 citations*](https://md.research.elamur.ai/free/en/papers/lu-2019-vilbert-pretraining-task-agnostic-visiolinguistic/)
127. [**Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification**Peng Zhou, Wei Shi, Jun Tian, et al.*2016 · 2,216 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2016-attention-based-bidirectional-long-short/)
128. [**Automatic Labeling of Semantic Roles**Daniel Gildea, Daniel Jurafsky*2002 · 2,216 citations*](https://md.research.elamur.ai/free/en/papers/gildea-2002-automatic-labeling-semantic-roles/)
129. [**Emergent Abilities of Large Language Models**Jason Wei, Yi Tay, Rishi Bommasani, et al.*2022 · 2,215 citations*](https://md.research.elamur.ai/free/en/papers/wei-2022-emergent-abilities-large-language-models/)
130. [**FEVER: a Large-scale Dataset for Fact Extraction and VERification**James Thorne, Andreas Vlachos, Christos Christodoulopoulos, et al.*2018 · 2,205 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-fever-large-scale-dataset-fact/)
131. [**Reflexion: Language Agents with Verbal Reinforcement Learning**Noah Shinn, Federico Cassano, Edward Berman, et al.*2023 · 2,202 citations*](https://md.research.elamur.ai/free/en/papers/shinn-2023-reflexion-language-agents-verbal-reinforcement/)
132. [**SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems**Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.*2019 · 2,187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/)
133. [**WordNet: A Lexical Database for English**George A. Miller*1994 · 2,179 citations*](https://md.research.elamur.ai/free/en/papers/miller-1994-wordnet/)
134. [**Multimodal Transformer for Unaligned Multimodal Language Sequences**Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, et al.*2019 · 2,170 citations*](https://md.research.elamur.ai/free/en/papers/tsai-2019-multimodal-transformer-unaligned-multimodal-language/)
135. [**Probabilistic Latent Semantic Analysis**Thomas Hofmann*1999 · 2,145 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-1999-probabilistic-latent-semantic-analysis/)
136. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
137. [**BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models**Junnan Li, Dongxu Li, Silvio Savarese, et al.*2023 · 2,114 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-blip-2-bootstrapping-language-image/)
138. [**Flamingo: a Visual Language Model for Few-Shot Learning**Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.*2022 · 2,108 citations*](https://md.research.elamur.ai/free/en/papers/alayrac-2022-flamingo-visual-language-model-few/)
139. [**chrF: character n-gram F-score for automatic MT evaluation**Maja Popović*2015 · 2,105 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/)
140. [**Centering: A Framework for Modeling the Local Coherence of Discourse**Barbara J. Grosz, Aravind K. Joshi, Scott Weinstein*1995 · 2,101 citations*](https://md.research.elamur.ai/free/en/papers/grosz-1995-centering-framework-modeling-local-coherence/)
141. [**How Multilingual is Multilingual BERT?**Telmo Pires, Eva Schlinger, Dan Garrette*2019 · 2,095 citations*](https://md.research.elamur.ai/free/en/papers/pires-2019-how-multilingual-is-multilingual-bert/)
142. [**Automatic Retrieval and Clustering of Similar Words**Dekang Lin*1998 · 2,060 citations*](https://md.research.elamur.ai/free/en/papers/lin-1998-automatic-retrieval-clustering-similar-words/)
143. [**A Maximum-Entropy-Inspired Parser**Eugene Charniak*2000 · 2,049 citations*](https://md.research.elamur.ai/free/en/papers/charniak-2000-maximum-entropy-inspired-parser/)
144. [**TruthfulQA: Measuring How Models Mimic Human Falsehoods**Stephanie Lin, Jacob Hilton, Owain Evans*2022 · 2,047 citations*](https://md.research.elamur.ai/free/en/papers/lin-2022-truthfulqa-measuring-how-models-mimic/)
145. [**Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings**Tolga Bolukbasi, Kai-Wei Chang, James Zou, et al.*2016 · 2,038 citations*](https://md.research.elamur.ai/free/en/papers/bolukbasi-2016-man-computer-programmer-woman-homemaker/)
146. [**Reading Tea Leaves: How Humans Interpret Topic Models**Jonathan Chang, Jordan Boyd-Graber, Sean Gerrish, et al.*2009 · 2,037 citations*](https://md.research.elamur.ai/free/en/papers/chang-2009-reading-tea-leaves-humans-interpret-topic/)
147. [**Information structure in discourse: Towards an integrated formal theory of pragmatics**Craige Roberts*2012 · 2,020 citations*](https://md.research.elamur.ai/free/en/papers/roberts-2012-information-structure-discourse-towards-integrated/)
148. [**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/)
149. [**GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering**Drew A. Hudson, Christopher D. Manning*2019 · 1,997 citations*](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/)
150. [**BERT Rediscovers the Classical NLP Pipeline**Ian Tenney, Dipanjan Das, Ellie Pavlick*2019 · 1,993 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-bert-rediscovers-classical-nlp-pipeline/)
151. [**Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics**Chin-Yew Lin, Eduard Hovy*2003 · 1,967 citations*](https://md.research.elamur.ai/free/en/papers/lin-2003-automatic-evaluation-summaries-n-gram/)
152. [**Bidirectional Attention Flow for Machine Comprehension**Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, et al.*2016 · 1,956 citations*](https://md.research.elamur.ai/free/en/papers/seo-2016-bidirectional-attention-flow-machine-comprehension/)
153. [**Making Pre-trained Language Models Better Few-shot Learners**Tianyu Gao, Adam Fisch, Danqi Chen*2021 · 1,952 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-making-pre-trained-language-models/)
154. [**Knowledge Graph Embedding via Dynamic Mapping Matrix**Guoliang Ji, Shizhu He, Liheng Xu, et al.*2015 · 1,936 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-knowledge-graph-embedding-dynamic-mapping/)
155. [**Adversarial Examples for Evaluating Reading Comprehension Systems**Robin Jia, Percy Liang*2017 · 1,935 citations*](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/)
156. [**Abstract Meaning Representation for Sembanking**Laura Banarescu, Claire Bonial, Shu Cai, et al.*2013 · 1,915 citations*](https://md.research.elamur.ai/free/en/papers/banarescu-2013-abstract-meaning-representation-sembanking/)
157. [**Extracting Product Features and Opinions from Reviews**Ana-Maria Popescu, Oren Etzioni*2005 · 1,904 citations*](https://md.research.elamur.ai/free/en/papers/popescu-2005-extracting-product-features-opinions-reviews/)
158. [**Incorporating Copying Mechanism in Sequence-to-Sequence Learning**Jiatao Gu, Zhengdong Lu, Hang Li, et al.*2016 · 1,895 citations*](https://md.research.elamur.ai/free/en/papers/gu-2016-incorporating-copying-mechanism-sequence-sequence/)
159. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,879 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/)
160. [**A Language Modeling Approach to Information Retrieval**Jay M. Ponte, W. Bruce Croft*1998 · 1,867 citations*](https://md.research.elamur.ai/free/en/papers/ponte-1998-language-modeling-approach-information/)
161. [**Microsoft COCO Captions: Data Collection and Evaluation Server**Xinlei Chen, Hao Fang, Tsung-Yi Lin, et al.*2015 · 1,859 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-microsoft-coco-captions-data-collection/)
162. [**Character-Aware Neural Language Models**Yoon Kim, Yacine Jernite, David Sontag, et al.*2015 · 1,852 citations*](https://md.research.elamur.ai/free/en/papers/kim-2015-character-aware-neural-language-models/)
163. [**Personalizing Dialogue Agents: I have a dog, do you have pets too?**Saizheng Zhang, Emily Dinan, Jack Urbanek, et al.*2018 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-personalizing-dialogue-agents-i-have/)
164. [**Automatically Constructing a Corpus of Sentential Paraphrases**William B. Dolan, Chris Brockett*2005 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/dolan-2005-automatically-constructing-corpus-sentential-paraphrases/)
165. [**Design Challenges and Misconceptions in Named Entity Recognition**Lev Ratinov, Dan Roth*2009 · 1,836 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
166. [**PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization**Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al.*2019 · 1,806 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/)
167. [**AllenNLP: A Deep Semantic Natural Language Processing Platform**Matt Gardner, Joel Grus, Mark Neumann, et al.*2018 · 1,804 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2018-allennlp-deep-semantic-natural-language/)
168. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,800 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/)
169. [**Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference**Timo Schick, Hinrich Schütze*2021 · 1,796 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/)
170. [**The Penn Discourse TreeBank 2.0.**Rashmi Prasad, Nikhil Dinesh, Alan Lee, et al.*2008 · 1,793 citations*](https://md.research.elamur.ai/free/en/papers/prasad-2008-penn-discourse-treebank-2-0/)
171. [**Domain Adaptation with Structural Correspondence Learning**John Blitzer, Ryan McDonald, Fernando Pereira*2006 · 1,792 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2006-domain-adaptation-structural-correspondence-learning/)
172. [**What Does BERT Learn about the Structure of Language?**Ganesh Jawahar, Benoît Sagot, Djamé Seddah*2019 · 1,789 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2019-what-does-bert-learn-about/)
173. [**COMET: A Neural Framework for MT Evaluation**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 1,784 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)
174. [**ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT**Omar Khattab, Matei Zaharia*2020 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/)
175. [**Attention-Based Models for Speech Recognition**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
176. [**Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging**Eric Brill*1995 · 1,774 citations*](https://md.research.elamur.ai/free/en/papers/brill-1995-transformation-based-error-driven-learning/)
177. [**A Structured Self-attentive Sentence Embedding**Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.*2017 · 1,773 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/)
178. [**Survey Article: Inter-Coder Agreement for Computational Linguistics**Ron Artstein, Massimo Poesio*2008 · 1,770 citations*](https://md.research.elamur.ai/free/en/papers/artstein-2008-survey-article-inter-coder-agreement/)
179. [**A Neural Conversational Model**Oriol Vinyals, Quoc Le*2015 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/vinyals-2015-neural-conversational-model/)
180. [**KenLM: Faster and Smaller Language Model Queries**Kenneth Heafield*2011 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/heafield-2011-kenlm-faster-smaller-language-model/)
181. [**TnT – A Statistical Part-of-Speech Tagger**Thorsten Brants*2000 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/)
182. [**Pre-trained Models for Natural Language Processing: A Survey**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,740 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
183. [**Universal Dependencies v1: A Multilingual Treebank Collection**Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, et al.*2016 · 1,739 citations*](https://md.research.elamur.ai/free/en/papers/nivre-2016-universal-dependencies-v1-multilingual-treebank/)
184. [**BERTopic: Neural topic modeling with a class-based TF-IDF procedure**Maarten Grootendorst*2022 · 1,729 citations*](https://md.research.elamur.ai/free/en/papers/grootendorst-2022-bertopic-neural-topic-modeling-class/)
185. [**Language (Technology) is Power: A Critical Survey of “Bias” in NLP**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,700 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/)
186. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,695 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
187. [**A Hierarchical Phrase-Based Model for Statistical Machine Translation**David Chiang*2005 · 1,683 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2005-hierarchical-phrase-based-model-statistical/)
188. [**Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors**Marco Baroni, Georgiana Dinu, Germán Kruszewski*2014 · 1,678 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2014-don-t-count-predict-systematic/)
189. [**Determining the Sentiment of Opinions**Soo-Min Kim, Eduard Hovy*2004 · 1,677 citations*](https://md.research.elamur.ai/free/en/papers/kim-2004-determining-sentiment-opinions/)
190. [**Document Modeling with Gated Recurrent Neural Network for Sentiment Classification**Duyu Tang, Bing Qin, Ting Liu*2015 · 1,675 citations*](https://md.research.elamur.ai/free/en/papers/tang-2015-document-modeling-gated-recurrent-neural/)
191. [**Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering**Gautier Izacard, Edouard Grave*2021 · 1,674 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-leveraging-passage-retrieval-generative-models/)
192. [**Pointer Sentinel Mixture Models**Stephen Merity, Caiming Xiong, James Bradbury, et al.*2016 · 1,669 citations*](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/)
193. [**MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations**Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, et al.*2018 · 1,668 citations*](https://md.research.elamur.ai/free/en/papers/poria-2018-meld-multimodal-multi-party-dataset/)
194. [**Relation Classification via Convolutional Deep Neural Network**Daojian Zeng, Kang Liu, Siwei Lai, et al.*2014 · 1,659 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2014-relation-classification-convolutional-deep-neural/)
195. [**SemEval-2016 Task 5: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al.*2016 · 1,656 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2016-semeval-2016-task-5-aspect/)
196. [**Retrieval-Augmented Generation for Large Language Models: A Survey**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,647 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
197. [**Learning Question Classifiers**Xin Li, Dan Roth*2002 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/li-2002-learning-question-classifiers/)
198. [**Qwen Technical Report**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,643 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/)
199. [**Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference**R. Thomas McCoy, Ellie Pavlick, Tal Linzen*2019 · 1,630 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)
200. [**Hierarchical Phrase-Based Translation**David Chiang*2007 · 1,628 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2007-hierarchical-phrase-based-translation/)
201. [**A Deep Reinforced Model for Abstractive Summarization**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,626 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
202. [**SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation**Felix Hill, Roi Reichart, Anna Korhonen*2015 · 1,622 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-simlex-999-evaluating-semantic-models/)
203. [**RACE: Large-scale ReAding Comprehension Dataset From Examinations**Guokun Lai, Qizhe Xie, Hanxiao Liu, et al.*2017 · 1,619 citations*](https://md.research.elamur.ai/free/en/papers/lai-2017-race-large-scale-reading-comprehension/)
204. [**A Simple Rule-Based Part of Speech Tagger**Eric Brill*1992 · 1,618 citations*](https://md.research.elamur.ai/free/en/papers/brill-1992-simple-rule-based-part-speech/)
205. [**Universal Sentence Encoder**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,616 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder/)
206. [**Evaluating WordNet-based Measures of Lexical Semantic Relatedness**Alexander Budanitsky, Graeme Hirst*2006 · 1,610 citations*](https://md.research.elamur.ai/free/en/papers/budanitsky-2006-evaluating-wordnet-based-measures-lexical/)
207. [**Recurrent Continuous Translation Models**Nal Kalchbrenner, Phil Blunsom*2013 · 1,597 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2013-recurrent-continuous-translation-models/)
208. [**End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures**Makoto Miwa, Mohit Bansal*2016 · 1,596 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/)
209. [**A Decomposable Attention Model for Natural Language Inference**Ankur Parikh, Oscar Täckström, Dipanjan Das, et al.*2016 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/parikh-2016-decomposable-attention-model-natural-language/)
210. [**Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,582 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/)
211. [**Multitask Prompted Training Enables Zero-Shot Task Generalization**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,577 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
212. [**Deep Speech: Scaling up end-to-end speech recognition**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,575 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
213. [**WordNet Affect: an Affective Extension of WordNet**Carlo Strapparava, Alessandro Valitutti*2004 · 1,573 citations*](https://md.research.elamur.ai/free/en/papers/strapparava-2004-wordnet-affect-affective-extension-wordnet/)
214. [**SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents**Ramesh Nallapati, Feifei Zhai, Bowen Zhou*2016 · 1,566 citations*](https://md.research.elamur.ai/free/en/papers/nallapati-2016-summarunner-recurrent-neural-network-based/)
215. [**Semantic Compositionality through Recursive Matrix-Vector Spaces**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,559 citations*](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
216. [**A Maximum Entropy Model for Part-Of-Speech Tagging**Adwait Ratnaparkhi*1996 · 1,554 citations*](https://md.research.elamur.ai/free/en/papers/ratnaparkhi-1996-maximum-entropy-model-part-speech/)
217. [**Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,548 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/)
218. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/)
219. [**Universal Sentence Encoder for English**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,544 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder-english/)
220. [**Competition-Level Code Generation with AlphaCode**Yujia Li, David Choi, Junyoung Chung, et al.*2022 · 1,543 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-competition-level-code-generation-alphacode/)
221. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,541 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
222. [**ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks**Fabrizio Gilardi, Meysam Alizadeh, Maël Kubli*2023 · 1,532 citations*](https://md.research.elamur.ai/free/en/papers/gilardi-2023-chatgpt-outperforms-crowd-workers-text/)
223. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
224. [**Efficient Transformers: A Survey**Yi Tay, Mostafa Dehghani, Dara Bahri, et al.*2020 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/)
225. [**Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,511 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/)

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