---
title: "Artificial Intelligence — papers, page 3"
description: "Artificial Intelligence: 7,180 papers of the Elamur Research library · page 3 of 73 · 126–225, the most cited first — our summary of each, its ideas…"
canonical: "https://research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/3/"
---
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# 🤖 Artificial Intelligence

7,180 papers · page 3 of 73 · 126–225 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Artificial Intelligence is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Natural Language Processing Techniques», «Topic Modeling», «Speech and dialogue systems».

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/2/) [1](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) [2](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/2/) **3** [4](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/4/) … [73](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/73/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/page/4/)

126. [**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/)
127. [**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/)
128. [**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/)
129. [**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/)
130. [**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/)
131. [**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/)
132. [**hdbscan: Hierarchical density based clustering**Leland McInnes, John Healy, Steve Astels*2017 · 2,932 citations*](https://md.research.elamur.ai/free/en/papers/mcinnes-2017-hdbscan-hierarchical-density-clustering/)
133. [**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/)
134. [**Fitting Linear Mixed-Effects Models Using lme4**Douglas Bates, Martin Mächler, Ben Bolker, et al.*2015 · 2,924 citations*](https://md.research.elamur.ai/free/en/papers/bates-2015-fitting-linear-mixed-effects-models/)
135. [**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/)
136. [**Twitter as a Corpus for Sentiment Analysis and Opinion Mining**Alexander Pak, Patrick Paroubek*2010 · 2,905 citations*](https://md.research.elamur.ai/free/en/papers/pak-2010-twitter-as-corpus-sentiment-analysis/)
137. [**Learning to Rank using Gradient Descent**Chris Burges, Tal Shaked, Erin Renshaw, et al.*2005 · 2,896 citations*](https://md.research.elamur.ai/free/en/papers/burges-2005-learning-rank-using-gradient/)
138. [**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/)
139. [**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/)
140. [**What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?**Alex Kendall, Yarin Gal*2017 · 2,844 citations*](https://md.research.elamur.ai/free/en/papers/kendall-2017-uncertainties-need-bayesian-deep-learning/)
141. [**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/)
142. [**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/)
143. [**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/)
144. [**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/)
145. [**Efficient Memory Management for Large Language Model Serving with PagedAttention**Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.*2023 · 2,738 citations*](https://md.research.elamur.ai/free/en/papers/kwon-2023-efficient-memory-management-large-language/)
146. [**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/)
147. [**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/)
148. [**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/)
149. [**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/)
150. [**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/)
151. [**PaLM: Scaling Language Modeling with Pathways**Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.*2022 · 2,603 citations*](https://md.research.elamur.ai/free/en/papers/chowdhery-2022-palm-scaling-language-modeling-pathways/)
152. [**Stochastic Backpropagation and Approximate Inference in Deep Generative Models**Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra*2014 · 2,586 citations*](https://md.research.elamur.ai/free/en/papers/rezende-2014-stochastic-backpropagation-approximate-inference-deep/)
153. [**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/)
154. [**Improved Baselines with Visual Instruction Tuning**Haotian Liu, Chunyuan Li, Yuheng Li, et al.*2023 · 2,557 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-improved-baselines-visual-instruction-tuning/)
155. [**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/)
156. [**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/)
157. [**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/)
158. [**An Overview of Multi-Task Learning in Deep Neural Networks**Sebastian Ruder*2017 · 2,506 citations*](https://md.research.elamur.ai/free/en/papers/ruder-2017-overview-multi-task-learning-deep/)
159. [**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/)
160. [**ReAct: Synergizing Reasoning and Acting in Language Models**Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.*2022 · 2,493 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-react-synergizing-reasoning-acting-language/)
161. [**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/)
162. [**Direct Preference Optimization: Your Language Model is Secretly a Reward Model**Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.*2023 · 2,478 citations*](https://md.research.elamur.ai/free/en/papers/rafailov-2023-direct-preference-optimization-language-model/)
163. [**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/)
164. [**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/)
165. [**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/)
166. [**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/)
167. [**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/)
168. [**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/)
169. [**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/)
170. [**Learning Important Features Through Propagating Activation Differences**Avanti Shrikumar, Peyton Greenside, Anshul Kundaje*2017 · 2,377 citations*](https://md.research.elamur.ai/free/en/papers/shrikumar-2017-learning-important-features-through-propagating/)
171. [**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/)
172. [**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/)
173. [**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/)
174. [**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/)
175. [**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/)
176. [**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/)
177. [**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/)
178. [**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/)
179. [**Relational inductive biases, deep learning, and graph networks**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,285 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
180. [**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/)
181. [**Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)**Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter*2015 · 2,274 citations*](https://md.research.elamur.ai/free/en/papers/clevert-2015-fast-accurate-deep-network-learning/)
182. [**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/)
183. [**Reading Wikipedia to Answer Open-Domain Questions**Danqi Chen, Adam Fisch, Jason Weston, et al.*2017 · 2,250 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-reading-wikipedia-answer-open-domain/)
184. [**Equality of Opportunity in Supervised Learning**Moritz Hardt, Eric Price, Nathan Srebro*2016 · 2,224 citations*](https://md.research.elamur.ai/free/en/papers/hardt-2016-equality-opportunity-supervised-learning/)
185. [**GPT-4o System Card**OpenAI, Aaron Hurst, Adam Lerer, et al.*2024 · 2,221 citations*](https://md.research.elamur.ai/free/en/papers/openai-2024-gpt-4o-system-card/)
186. [**Enriching Word Vectors with Subword Information**Piotr Bojanowski, Edouard Grave, Armand Joulin, et al.*2017 · 2,218 citations*](https://md.research.elamur.ai/free/en/papers/bojanowski-2017-enriching-word-vectors-subword-information/)
187. [**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/)
188. [**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/)
189. [**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/)
190. [**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/)
191. [**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/)
192. [**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/)
193. [**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/)
194. [**WordNet: A Lexical Database for English**George A. Miller*1994 · 2,179 citations*](https://md.research.elamur.ai/free/en/papers/miller-1994-wordnet/)
195. [**Scaling Instruction-Finetuned Language Models**Hyung Won Chung, Le Hou, Shayne Longpre, et al.*2022 · 2,176 citations*](https://md.research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/)
196. [**Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter**Zeerak Waseem, Dirk Hovy*2016 · 2,158 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-hateful-symbols-or-hateful-people/)
197. [**Probabilistic Latent Semantic Analysis**Thomas Hofmann*1999 · 2,145 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-1999-probabilistic-latent-semantic-analysis/)
198. [**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/)
199. [**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/)
200. [**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/)
201. [**Tensor Fusion Network for Multimodal Sentiment Analysis**Amir Zadeh, Minghai Chen, Soujanya Poria, et al.*2017 · 2,107 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2017-tensor-fusion-network-multimodal-sentiment/)
202. [**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/)
203. [**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/)
204. [**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/)
205. [**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/)
206. [**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/)
207. [**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/)
208. [**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/)
209. [**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/)
210. [**Toolformer: Language Models Can Teach Themselves to Use Tools**Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, et al.*2023 · 2,020 citations*](https://md.research.elamur.ai/free/en/papers/schick-2023-toolformer-language-models-can-teach/)
211. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,013 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
212. [**Knowledge Graphs**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,011 citations*](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/)
213. [**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/)
214. [**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/)
215. [**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/)
216. [**MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems**Tianqi Chen, Mu Li, Yutian Li, et al.*2015 · 1,981 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-mxnet-flexible-efficient-machine-learning/)
217. [**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/)
218. [**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/)
219. [**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/)
220. [**An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale**Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, et al.*2020 · 1,947 citations*](https://md.research.elamur.ai/free/en/papers/dosovitskiy-2020-image-worth-16x16-words-transformers/)
221. [**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/)
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