---
title: "Who cites Deep Residual — page 2 — 5,237 citing papers"
description: "5,237 papers of the Elamur Research library cite «Deep Residual Learning for Image Recognition», found in their bibliographies · page 2 of 4…"
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---
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# Who cites «Deep Residual Learning for Image Recognition»

5,237 papers of our library cite it (of the 149,439 whose bibliographies we read) · 331 with a page here, the most cited first · page 2 of 4 · 101–200 · [← back to «Deep Residual Learning for Image Recognition»](https://md.research.elamur.ai/free/en/papers/he-2015-deep-residual-learning-image-recognition/)

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101. [**OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework arXiv:2202.03052**Peng Wang, An Yang, Rui Men, et al.*2022 · 467 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-ofa-unifying-architectures-tasks-modalities/)
102. **[CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X](https://md.research.elamur.ai/free/en/papers/zheng-2023-codegeex-pre-trained-model-code/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Qinkai Zheng, Xiao Xia, Xu Zou, et al.*2023 · 465 citations*
103. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning arXiv:1612.06890**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 464 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
104. **[Exploring Pre-trained Language Models for Event Extraction and Generation](https://md.research.elamur.ai/free/en/papers/yang-2019-exploring-pre-trained-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sen Yang, Dawei Feng, Linbo Qiao, et al.*2019 · 454 citations*
105. **[HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization](https://md.research.elamur.ai/free/en/papers/zhang-2019-hibert-document-level-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingxing Zhang, Furu Wei, Ming Zhou*2019 · 451 citations*
106. [**Pay Less Attention with Lightweight and Dynamic Convolutions arXiv:1901.10430**Felix Wu, Angela Fan, Alexei Baevski, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/)
107. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks arXiv:2312.14238**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 435 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
108. [**Benchmarking Neural Network Robustness to Common Corruptions and Perturbations arXiv:1903.12261**Dan Hendrycks, Thomas Dietterich*2019 · 434 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2019-benchmarking-neural-network-robustness-common/)
109. **[WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents](https://md.research.elamur.ai/free/en/papers/yao-2022-webshop-towards-scalable-real-world/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shunyu Yao, Howard Chen, John Yang, et al.*2022 · 420 citations*
110. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
111. **[Exploiting BERT for End-to-End Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/li-2019-exploiting-bert-end-end-aspect/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Xin Li, Lidong Bing, Wenxuan Zhang, et al.*2019 · 417 citations*
112. **[A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://md.research.elamur.ai/free/en/papers/sharma-2020-computational-approach-understanding-empathy-expressed/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ashish Sharma, Adam Miner, David Atkins, et al.*2020 · 412 citations*
113. **[Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network](https://md.research.elamur.ai/free/en/papers/zhou-2018-multi-turn-response-selection-chatbots/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyang Zhou, Lu Li, Daxiang Dong, et al.*2018 · 410 citations*
114. [**Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding arXiv:1810.02338**Kexin Yi, Jiajun Wu, Chuang Gan, et al.*2018 · 407 citations*](https://md.research.elamur.ai/free/en/papers/yi-2018-neural-symbolic-vqa-disentangling-reasoning/)
115. [**FiLM: Visual Reasoning with a General Conditioning Layer arXiv:1709.07871**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 400 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
116. [**A Simple Language Model for Task-Oriented Dialogue arXiv:2005.00796**Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, et al.*2020 · 399 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-asl-2020-simple-language-model-task-oriented/)
117. **[A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 395 citations*
118. [**Green AI arXiv:1907.10597**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 389 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
119. **[Deep Semantic Role Labeling with Self-Attention](https://md.research.elamur.ai/free/en/papers/tan-2017-deep-semantic-role-labeling-self/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Zhixing Tan, Mingxuan Wang, Jun Xie, et al.*2017 · 387 citations*
120. **[English Conversational Telephone Speech Recognition by Humans and Machines](https://md.research.elamur.ai/free/en/papers/saon-2017-english-conversational-telephone-speech-recognition/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**George Saon, Gakuto Kurata, Tom Sercu, et al.*2017 · 385 citations*
121. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
122. [**Averaging Weights Leads to Wider Optima and Better Generalization arXiv:1803.05407**Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, et al.*2018 · 366 citations*](https://md.research.elamur.ai/free/en/papers/izmailov-2018-averaging-weights-leads-wider-optima/)
123. **[Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds](https://md.research.elamur.ai/free/en/papers/ash-2019-deep-batch-active-learning-diverse/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Jordan T. Ash, Chicheng Zhang, Akshay Krishnamurthy, et al.*2019 · 362 citations*
124. **[Visual Attention Model for Name Tagging in Multimodal Social Media](https://md.research.elamur.ai/free/en/papers/lu-2018-visual-attention-model-name-tagging/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Di Lu, Leonardo Neves, Vitor Carvalho, et al.*2018 · 361 citations*
125. **[Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout](https://md.research.elamur.ai/free/en/papers/tan-2019-learning-navigate-unseen-environments-back/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hao Tan, Licheng Yu, Mohit Bansal*2019 · 358 citations*
126. **[A Shared Task on Multimodal Machine Translation and Crosslingual Image Description](https://md.research.elamur.ai/free/en/papers/specia-2016-shared-task-multimodal-machine-translation/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Lucia Specia, Stella Frank, Khalil Sima'an, et al.*2016 · 357 citations*
127. **[Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction](https://md.research.elamur.ai/free/en/papers/verga-2018-simultaneously-self-attending-all-mentions/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Verga, Emma Strubell, Andrew McCallum*2018 · 353 citations*
128. [**PyTorch Distributed: Experiences on Accelerating Data Parallel Training arXiv:2006.15704**Shen Li, Yanli Zhao, Rohan Varma, et al.*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-pytorch-distributed-experiences-accelerating-data/)
129. [**Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes arXiv:1807.11205**Xianyan Jia, Shutao Song, Wei He, et al.*2018 · 348 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-highly-scalable-deep-learning-training/)
130. **[Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space](https://md.research.elamur.ai/free/en/papers/geva-2022-transformer-feed-forward-layers-build/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mor Geva, Avi Caciularu, Kevin Ro Wang, et al.*2022 · 346 citations*
131. **[Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer](https://md.research.elamur.ai/free/en/papers/yu-2020-improving-multimodal-named-entity-recognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianfei Yu, Jing Jiang, Li Yang, et al.*2020 · 342 citations*
132. **[Neural Paraphrase Generation with Stacked Residual LSTM Networks](https://md.research.elamur.ai/free/en/papers/prakash-2016-neural-paraphrase-generation-stacked-residual/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Aaditya Prakash, Sadid A. Hasan, Kathy Lee, et al.*2016 · 337 citations*
133. [**Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions arXiv:1802.04730**Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.*2018 · 323 citations*](https://md.research.elamur.ai/free/en/papers/vasilache-2018-tensor-comprehensions-framework-agnostic-high/)
134. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 322 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
135. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
136. **[Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 320 citations*
137. [**Multimodal Chain-of-Thought Reasoning in Language Models arXiv:2302.00923**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 308 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
138. **[UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 308 citations*
139. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
140. **[xLSTM: Extended Long Short-Term Memory](https://md.research.elamur.ai/free/en/papers/beck-2024-xlstm-extended-long-short-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.*2024 · 296 citations*
141. **[Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jue Wang, Wei Lu*2020 · 288 citations*
142. [**Cloze-driven Pretraining of Self-attention Networks arXiv:1903.07785**Alexei Baevski, Sergey Edunov, Yinhan Liu, et al.*2019 · 286 citations*](https://md.research.elamur.ai/free/en/papers/baevski-2019-cloze-driven-pretraining-self-attention/)
143. **[Guided Open Vocabulary Image Captioning with Constrained Beam Search](https://md.research.elamur.ai/free/en/papers/anderson-2017-guided-open-vocabulary-image-captioning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peter Anderson, Basura Fernando, Mark Johnson, et al.*2017 · 286 citations*
144. [**Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models arXiv:1610.02424**Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, et al.*2016 · 282 citations*](https://md.research.elamur.ai/free/en/papers/vijayakumar-2016-diverse-beam-search-decoding-diverse/)
145. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
146. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
147. **[Reinforced Mnemonic Reader for Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/hu-2017-reinforced-mnemonic-reader-machine-reading/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Minghao Hu, Yuxing Peng, Zhen Huang, et al.*2017 · 273 citations*
148. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models arXiv:2309.03883**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
149. [**Perceiver: General Perception with Iterative Attention arXiv:2103.03206**Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.*2021 · 269 citations*](https://md.research.elamur.ai/free/en/papers/jaegle-2021-perceiver-general-perception-iterative-attention/)
150. **[Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhou-2016-deep-recurrent-models-fast-forward/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jie Zhou, Ying Cao, Xuguang Wang, et al.*2016 · 265 citations*
151. **[SemEval-2020 Task 8: Memotion Analysis- the Visuo-Lingual Metaphor!](https://md.research.elamur.ai/free/en/papers/sharma-2020-semeval-2020-task-8-memotion/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Chhavi Sharma, Deepesh Bhageria, William Scott, et al.*2020 · 261 citations*
152. **[Sparse GPU Kernels for Deep Learning](https://md.research.elamur.ai/free/en/papers/gale-2020-sparse-gpu-kernels-deep-learning/) [2012 International Conference for High Performance Computing, Networking, Storage and Analysis](https://md.research.elamur.ai/free/en/venues/2012-international-conference-for-high-performance-computing-networking-storage/)**Trevor Gale, Matei Zaharia, Cliff Young, et al.*2020 · 259 citations*
153. [**Once-for-All: Train One Network and Specialize it for Efficient Deployment arXiv:1908.09791**Han Cai, Chuang Gan, Tianzhe Wang, et al.*2019 · 252 citations*](https://md.research.elamur.ai/free/en/papers/cai-2019-once-all-train-one-network/)
154. [**Improved Knowledge Distillation via Teacher Assistant arXiv:1902.03393**Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, et al.*2019 · 248 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2019-improved-knowledge-distillation-teacher-assistant/)
155. **[MedDialog: Large-scale Medical Dialogue Datasets](https://md.research.elamur.ai/free/en/papers/zeng-2020-meddialog-large-scale-medical-dialogue/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guangtao Zeng, Wenmian Yang, Zeqian Ju, et al.*2020 · 247 citations*
156. **[EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing](https://md.research.elamur.ai/free/en/papers/dong-2019-editnts-neural-programmer-interpreter-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Dong, Zichao Li, Mehdi Rezagholizadeh, et al.*2019 · 244 citations*
157. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
158. [**The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision arXiv:1904.12584**Jiayuan Mao, Chuang Gan, Pushmeet Kohli, et al.*2019 · 241 citations*](https://md.research.elamur.ai/free/en/papers/mao-2019-neuro-symbolic-concept-learner-interpreting/)
159. **[BERT-of-Theseus: Compressing BERT by Progressive Module Replacing](https://md.research.elamur.ai/free/en/papers/xu-2020-bert-theseus-compressing-bert-progressive/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Canwen Xu, Wangchunshu Zhou, Tao Ge, et al.*2020 · 240 citations*
160. [**FigureQA: An Annotated Figure Dataset for Visual Reasoning arXiv:1710.07300**Samira Ebrahimi Kahou, Vincent Michalski, Adam Atkinson, et al.*2017 · 240 citations*](https://md.research.elamur.ai/free/en/papers/kahou-2017-figureqa-annotated-figure-dataset-visual/)
161. **[Towards Robust Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/cheng-2018-robust-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yong Cheng, Zhaopeng Tu, Fandong Meng, et al.*2018 · 238 citations*
162. **[Understanding the Difficulty of Training Transformers](https://md.research.elamur.ai/free/en/papers/liu-2020-understanding-difficulty-training-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyuan Liu, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 231 citations*
163. **[Findings of the Third Shared Task on Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/barrault-2018-findings-third-shared-task-multimodal/) [Conference on Machine Translation: Shared Task Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-shared-task-papers/)**Loïc Barrault, Fethi Bougares, Lucia Specia, et al.*2018 · 230 citations*
164. **[Towards Multimodal Sarcasm Detection (An \textitObviously Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-multimodal-sarcasm-detection-textitobviously-perfect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 228 citations*
165. **[DataComp: In search of the next generation of multimodal datasets](https://md.research.elamur.ai/free/en/papers/gadre-2023-datacomp-search-next-generation-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.*2023 · 224 citations*
166. [**Estimating Training Data Influence by Tracing Gradient Descent arXiv:2002.08484**Garima Pruthi, Frederick Liu, Mukund Sundararajan, et al.*2020 · 223 citations*](https://md.research.elamur.ai/free/en/papers/pruthi-2020-estimating-training-data-influence-tracing/)
167. **[Probing the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/caglayan-2019-probing-need-visual-context-multimodal/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al.*2019 · 217 citations*
168. [**Compositional Attention Networks for Machine Reasoning arXiv:1803.03067**Drew A. Hudson, Christopher D. Manning*2018 · 213 citations*](https://md.research.elamur.ai/free/en/papers/hudson-2018-compositional-attention-networks-machine-reasoning/)
169. **[Automated Concatenation of Embeddings for Structured Prediction](https://md.research.elamur.ai/free/en/papers/wang-2021-automated-concatenation-embeddings-structured-prediction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Wang, Yong Jiang, Nguyen Bach, et al.*2021 · 206 citations*
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