---
title: "Computer Vision and Pattern Recognition — papers, page 3"
description: "Computer Vision and Pattern Recognition: 1,029 papers of the Elamur Research library · page 3 of 12 · 126–225, the most cited first — our summary of each…"
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---
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# 👁️ Computer Vision and Pattern Recognition

1,029 papers · page 3 of 12 · 126–225 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Computer Vision and Pattern Recognition is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Multimodal Machine Learning Applications», «Advanced Neural Network Applications», «Handwritten Text Recognition Techniques».

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) [1](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) [2](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/2/) **3** [4](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/4/) … [12](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/12/) [next →](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/page/4/)

126. [**Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks**Yubo Chen, Liheng Xu, Kang Liu, et al.*2015 · 1,170 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-event-extraction-dynamic-multi-pooling/)
127. [**Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering**Yash Goyal, Tejas Khot, Douglas Summers-Stay, et al.*2016 · 1,169 citations*](https://md.research.elamur.ai/free/en/papers/goyal-2016-making-v-vqa-matter-elevating/)
128. [**Modeling Context in Referring Expressions**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,165 citations*](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/)
129. [**Generative Modeling by Estimating Gradients of the Data Distribution**Yang Song, Stefano Ermon*2019 · 1,155 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/)
130. [**Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps**Karen Simonyan, Andrea Vedaldi, Andrew Zisserman*2013 · 1,153 citations*](https://md.research.elamur.ai/free/en/papers/simonyan-2013-deep-inside-convolutional-networks-visualising/)
131. [**Least-to-most prompting enables complex reasoning in large language models***2022 · 1,143 citations*](https://md.research.elamur.ai/free/en/papers/al-2022-least-most-prompting-enables-complex/)
132. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
133. [**Very Deep Convolutional Networks for Text Classification**Alexis Conneau, Holger Schwenk, Loïc Barrault, et al.*2017 · 1,110 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2017-very-deep-convolutional-networks-text/)
134. [**MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models**Deyao Zhu, Jun Chen, Xiaoqian Shen, et al.*2023 · 1,105 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-minigpt-4-enhancing-vision-language/)
135. [**Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,094 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)
136. [**NewsQA: A Machine Comprehension Dataset**Adam Trischler, Tong Wang, Xingdi Yuan, et al.*2017 · 1,088 citations*](https://md.research.elamur.ai/free/en/papers/trischler-2017-newsqa-machine-comprehension-dataset/)
137. [**Neural Module Networks**Jacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.*2015 · 1,075 citations*](https://md.research.elamur.ai/free/en/papers/andreas-2015-neural-module-networks/)
138. [**A Survey on Multimodal Large Language Models**Shukang Yin, Chaoyou Fu, Sirui Zhao, et al.*2023 · 1,060 citations*](https://md.research.elamur.ai/free/en/papers/yin-2023-survey-multimodal-large-language-models/)
139. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,051 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
140. [**ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,048 citations*](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/)
141. [**Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints**Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al.*2017 · 1,030 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/)
142. [**The NarrativeQA Reading Comprehension Challenge**Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, et al.*2018 · 1,026 citations*](https://md.research.elamur.ai/free/en/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)
143. [**MTEB: Massive Text Embedding Benchmark**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,021 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/)
144. [**GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,012 citations*](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/)
145. [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,008 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/)
146. [**Classifier-Free Diffusion Guidance**Jonathan Ho, Tim Salimans*2022 · 1,007 citations*](https://md.research.elamur.ai/free/en/papers/ho-2022-classifier-free-diffusion-guidance/)
147. [**A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,006 citations*](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/)
148. [**K-BERT: Enabling Language Representation with Knowledge Graph**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,006 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/)
149. [**MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices**Zhiqing Sun, Hongkun Yu, Xiaodan Song, et al.*2020 · 1,003 citations*](https://md.research.elamur.ai/free/en/papers/sun-2020-mobilebert-compact-task-agnostic-bert/)
150. [**A Theoretically Grounded Application of Dropout in Recurrent Neural Networks**Yarin Gal, Zoubin Ghahramani*2015 · 1,001 citations*](https://md.research.elamur.ai/free/en/papers/gal-2015-theoretically-grounded-application-dropout-recurrent/)
151. [**Big Bird: Transformers for Longer Sequences**Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.*2020 · 992 citations*](https://md.research.elamur.ai/free/en/papers/zaheer-2020-big-bird-transformers-longer-sequences/)
152. [**Chinese NER Using Lattice LSTM**Yue Zhang, Jie Yang*2018 · 990 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-chinese-ner-lattice-lstm/)
153. [**Evaluating Object Hallucination in Large Vision-Language Models**Yifan Li, Yifan Du, Kun Zhou, et al.*2023 · 986 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)
154. [**PaLM 2 Technical Report**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 971 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
155. [**FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/)
156. [**Effective Use of Word Order for Text Categorization with Convolutional Neural Networks**Rie Johnson, Tong Zhang*2015 · 956 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2015-effective-use-word-order-text/)
157. [**ERNIE: Enhanced Representation through Knowledge Integration**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 949 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-enhanced-representation-through-knowledge/)
158. [**Qwen2.5-VL Technical Report**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 948 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
159. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
160. [**MPNet: Masked and Permuted Pre-training for Language Understanding**Kaitao Song, Xu Tan, Tao Qin, et al.*2020 · 944 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-mpnet-masked-permuted-pre-training/)
161. [**A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network**Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, et al.*2018 · 944 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2018-novel-embedding-model-knowledge-base/)
162. [**ImageBind: One Embedding Space To Bind Them All**Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, et al.*2023 · 943 citations*](https://md.research.elamur.ai/free/en/papers/girdhar-2023-imagebind-one-embedding-space-bind/)
163. [**Patient Knowledge Distillation for BERT Model Compression**Siqi Sun, Yu Cheng, Zhe Gan, et al.*2019 · 939 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-patient-knowledge-distillation-bert-model/)
164. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 936 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
165. [**Bilateral Multi-Perspective Matching for Natural Language Sentences**Zhiguo Wang, Wael Hamza, Radu Florian*2017 · 923 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-bilateral-multi-perspective-matching-natural/)
166. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
167. [**Visual7W: Grounded Question Answering in Images**Yuke Zhu, Oliver Groth, Michael Bernstein, et al.*2015 · 915 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2015-visual7w-grounded-question-answering-images/)
168. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 913 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
169. [**Learning to Ask: Neural Question Generation for Reading Comprehension**Xinya Du, Junru Shao, Claire Cardie*2017 · 913 citations*](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/)
170. [**Grounded Compositional Semantics for Finding and Describing Images with Sentences**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 909 citations*](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/)
171. [**MMBench: Is Your Multi-modal Model an All-around Player?**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 907 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/)
172. [**Representing Text for Joint Embedding of Text and Knowledge Bases**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 904 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/)
173. [**Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme**Suncong Zheng, Feng Wang, Hongyun Bao, et al.*2017 · 902 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2017-joint-extraction-entities-relations-based/)
174. [**LayoutLM: Pre-training of Text and Layout for Document Image Understanding**Yiheng Xu, Minghao Li, Lei Cui, et al.*2019 · 889 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-layoutlm-pre-training-text-layout/)
175. [**MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text**Matthew Richardson, Christopher J.C. Burges, Erin Renshaw*2013 · 873 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2013-mctest-challenge-dataset-open-domain/)
176. [**A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity**Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.*2023 · 866 citations*](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/)
177. [**Segment Anything**Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.*2023 · 865 citations*](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/)
178. [**Challenges in Data-to-Document Generation**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 846 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/)
179. [**TaPas: Weakly Supervised Table Parsing via Pre-training**Jonathan Herzig, Pawel Krzysztof Nowak, Thomas Müller, et al.*2020 · 844 citations*](https://md.research.elamur.ai/free/en/papers/herzig-2020-tapas-weakly-supervised-table-parsing/)
180. [**UNIFIEDQA: Crossing Format Boundaries with a Single QA System**Daniel Khashabi, Sewon Min, Tushar Khot, et al.*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/)
181. [**A Unified MRC Framework for Named Entity Recognition**Xiaoya Li, Jingrong Feng, Yuxian Meng, et al.*2020 · 833 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-unified-mrc-framework-named-entity/)
182. [**On the Sentence Embeddings from Pre-trained Language Models**Bohan Li, Hao Zhou, Junxian He, et al.*2020 · 830 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-sentence-embeddings-pre-trained-language/)
183. [**Unsupervised Dense Information Retrieval with Contrastive Learning**Gautier Izacard, Mathilde Caron, Lucas Hosseini, et al.*2021 · 824 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-unsupervised-dense-information-retrieval-contrastive/)
184. [**Gated Self-Matching Networks for Reading Comprehension and Question Answering**Wenhui Wang, Nan Yang, Furu Wei, et al.*2017 · 823 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/)
185. [**DocVQA: A Dataset for VQA on Document Images**Minesh Mathew, Dimosthenis Karatzas, C.V. Jawahar*2020 · 820 citations*](https://md.research.elamur.ai/free/en/papers/mathew-2020-docvqa-dataset-vqa-document-images/)
186. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 819 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
187. [**Entity, Relation, and Event Extraction with Contextualized Span Representations**David Wadden, Ulme Wennberg, Yi Luan, et al.*2019 · 818 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2019-entity-relation-event-extraction-contextualized/)
188. [**ImageNet Large Scale Visual Recognition Challenge**Olga Russakovsky, Jia Deng, Hao Su, et al.*2014 · 816 citations*](https://md.research.elamur.ai/free/en/papers/russakovsky-2014-imagenet-large-scale-visual-recognition/)
189. [**U-Net: Convolutional Networks for Biomedical Image Segmentation**Olaf Ronneberger, Philipp Fischer, Thomas Brox*2015 · 813 citations*](https://md.research.elamur.ai/free/en/papers/ronneberger-2015-u-net-convolutional-networks-biomedical/)
190. [**Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 806 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/)
191. [**Towards Reasoning in Large Language Models: A Survey**Jie Huang, Kevin Chen-Chuan Chang*2023 · 775 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)
192. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
193. [**Ask Me Anything: Dynamic Memory Networks for Natural Language Processing**Ankit Kumar, Ozan Irsoy, Peter Ondruska, et al.*2015 · 775 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2015-ask-me-anything-dynamic-memory/)
194. [**LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 774 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/)
195. [**Reformer: The Efficient Transformer**Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya*2020 · 774 citations*](https://md.research.elamur.ai/free/en/papers/kitaev-2020-reformer-efficient-transformer/)
196. [**ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision**Wonjae Kim, Bokyung Son, Ildoo Kim*2021 · 762 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-vilt-vision-language-transformer-convolution/)
197. [**Reproducible scaling laws for contrastive language-image learning**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 750 citations*](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/)
198. [**ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning**Ahmed Masry, Do Xuan Long, Jia Qing Tan, et al.*2022 · 744 citations*](https://md.research.elamur.ai/free/en/papers/masry-2022-chartqa-benchmark-question-answering-about/)
199. [**Integrating Multimodal Information in Large Pretrained Transformers**Wasifur Rahman, Md Kamrul Hasan, Sangwu Lee, et al.*2020 · 742 citations*](https://md.research.elamur.ai/free/en/papers/rahman-2020-integrating-multimodal-information-large-pretrained/)
200. [**Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps**Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al.*2020 · 735 citations*](https://md.research.elamur.ai/free/en/papers/ho-2020-constructing-multi-hop-qa-dataset/)
201. [**MLQA: Evaluating Cross-lingual Extractive Question Answering**Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al.*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/)
202. [**CIDEr: Consensus-based Image Description Evaluation**Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh*2014 · 733 citations*](https://md.research.elamur.ai/free/en/papers/vedantam-2014-cider-consensus-based-image-description/)
203. [**MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 731 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/)
204. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations**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/)
205. [**SoundStream: An End-to-End Neural Audio Codec**Neil Zeghidour, Alejandro Luebs, Ahmed Omran, et al.*2021 · 727 citations*](https://md.research.elamur.ai/free/en/papers/zeghidour-2021-soundstream-end-end-neural-audio/)
206. [**ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks**Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox*2019 · 724 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2019-alfred-benchmark-interpreting-grounded-instructions/)
207. [**Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions**Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, et al.*2022 · 711 citations*](https://md.research.elamur.ai/free/en/papers/trivedi-2022-interleaving-retrieval-chain-thought-reasoning/)
208. [**A Multiscale Visualization of Attention in the Transformer Model**Jesse Vig*2019 · 708 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-multiscale-visualization-attention-transformer-model/)
209. [**Style Transfer in Text: Exploration and Evaluation**Zhenxin Fu, Xiaoye Tan, Nanyun Peng, et al.*2017 · 701 citations*](https://md.research.elamur.ai/free/en/papers/fu-2017-style-transfer-text-exploration-evaluation/)
210. [**Capabilities of GPT-4 on Medical Challenge Problems**Harsha Nori, Nicholas King, Scott Mayer McKinney, et al.*2023 · 700 citations*](https://md.research.elamur.ai/free/en/papers/nori-2023-capabilities-gpt-4-medical-challenge/)
211. [**Advances in domain independent linear text segmentation**Freddy Y. Y. Choi*2000 · 694 citations*](https://md.research.elamur.ai/free/en/papers/choi-2000-advances-domain-independent-linear-text/)
212. [**The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations**Felix Hill, Antoine Bordes, Sumit Chopra, et al.*2015 · 693 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-goldilocks-principle-reading-children-s/)
213. [**TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages**Jonathan H. Clark, Eunsol Choi, Michael Collins, et al.*2020 · 691 citations*](https://md.research.elamur.ai/free/en/papers/clark-2020-tydi-qa-benchmark-information-seeking/)
214. [**GLTR: Statistical Detection and Visualization of Generated Text**Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush*2019 · 691 citations*](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/)
215. [**SPECTER: Document-level Representation Learning using Citation-informed Transformers**Arman Cohan, Sergey Feldman, Iz Beltagy, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/cohan-2020-specter-document-level-representation-learning/)
216. [**TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data**Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.*2020 · 690 citations*](https://md.research.elamur.ai/free/en/papers/yin-2020-tabert-pretraining-joint-understanding-textual/)
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