---
title: "Who cites Jurgen Schmidhuber — 1,133 papers of our library"
description: "1,133 papers of the Elamur Research library cite the works of Jurgen Schmidhuber, found in their bibliographies · page 1 of 2 · 1–100; the…"
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---
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# Who cites Jurgen Schmidhuber

1,218 citations of their works from 1,133 papers of our library (of the 149,439 whose bibliographies we read) · 199 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Jurgen Schmidhuber](https://md.research.elamur.ai/free/en/authors/jurgen-schmidhuber/)

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1. [**Sequence to Sequence Learning with Neural Networks arXiv:1409.3215**Ilya Sutskever, Oriol Vinyals, Quoc V. Le*2014 · 18,409 citations*](https://md.research.elamur.ai/free/en/papers/sutskever-2014-sequence-sequence-learning-neural-networks/)
2. [**Deep Residual Learning for Image Recognition arXiv:1512.03385**Kaiming He, Xiangyu Zhang, Shaoqing Ren, et al.*2015 · 9,425 citations*](https://md.research.elamur.ai/free/en/papers/he-2015-deep-residual-learning-image-recognition/)
3. **[LSTM: A Search Space Odyssey](https://md.research.elamur.ai/free/en/papers/greff-2015-lstm-search-space-odyssey/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Klaus Greff, Rupesh Kumar Srivastava, Jan Koutnik, et al.*2015 · 7,008 citations*
4. [**Character-level Convolutional Networks for Text Classification arXiv:1509.01626**Xiang Zhang, Junbo Zhao, Yann LeCun*2015 · 4,827 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2015-character-level-convolutional-networks-text/)
5. [**Neural Architecture Search with Reinforcement Learning arXiv:1611.01578**Barret Zoph, Quoc V. Le*2016 · 4,413 citations*](https://md.research.elamur.ai/free/en/papers/zoph-2016-neural-architecture-search-reinforcement-learning/)
6. [**Bidirectional LSTM-CRF Models for Sequence Tagging arXiv:1508.01991**Zhiheng Huang, Wei Xu, Kai Yu*2015 · 3,822 citations*](https://md.research.elamur.ai/free/en/papers/huang-2015-bidirectional-lstm-crf-models-sequence/)
7. [**ImageNet Classification with Deep Convolutional Neural Networks NeurIPS 2012**Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton*2012 · 2,801 citations*](https://md.research.elamur.ai/free/en/papers/krizhevsky-2012-imagenet-classification-deep-convolutional/)
8. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
9. **[Deep Networks with Stochastic Depth](https://md.research.elamur.ai/free/en/papers/huang-2016-deep-networks-stochastic-depth/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Gao Huang, Yu Sun, Zhuang Liu, et al.*2016 · 2,160 citations*
10. [**Bidirectional Attention Flow for Machine Comprehension arXiv:1611.01603**Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, et al.*2016 · 1,988 citations*](https://md.research.elamur.ai/free/en/papers/seo-2016-bidirectional-attention-flow-machine-comprehension/)
11. **[Incorporating Copying Mechanism in Sequence-to-Sequence Learning](https://md.research.elamur.ai/free/en/papers/gu-2016-incorporating-copying-mechanism-sequence-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatao Gu, Zhengdong Lu, Hang Li, et al.*2016 · 1,915 citations*
12. [**Pointer Sentinel Mixture Models arXiv:1609.07843**Stephen Merity, Caiming Xiong, James Bradbury, et al.*2016 · 1,733 citations*](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/)
13. **[End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Makoto Miwa, Mohit Bansal*2016 · 1,606 citations*
14. [**Deep Speech: Scaling up end-to-end speech recognition arXiv:1412.5567**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,600 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
15. [**Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer arXiv:1612.03928**Sergey Zagoruyko, Nikos Komodakis*2016 · 1,542 citations*](https://md.research.elamur.ai/free/en/papers/zagoruyko-2016-paying-more-attention-attention-improving/)
16. **[Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, et al.*2018 · 1,522 citations*
17. [**Sequence Transduction with Recurrent Neural Networks arXiv:1211.3711**Alex Graves*2012 · 1,433 citations*](https://md.research.elamur.ai/free/en/papers/graves-2012-sequence-transduction-recurrent-neural-networks/)
18. [**OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks arXiv:1312.6229**Pierre Sermanet, David Eigen, Xiang Zhang, et al.*2013 · 1,423 citations*](https://md.research.elamur.ai/free/en/papers/sermanet-2013-overfeat-integrated-recognition-localization-detection/)
19. **[Generation and Comprehension of Unambiguous Object Descriptions](https://md.research.elamur.ai/free/en/papers/mao-2015-generation-comprehension-unambiguous-object-descriptions/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Junhua Mao, Jonathan Huang, Alexander Toshev, et al.*2015 · 1,388 citations*
20. [**Deep Biaffine Attention for Neural Dependency Parsing**Timothy Dozat, Christopher D. Manning*2016 · 1,326 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2016-deep-biaffine-attention-neural-dependency/)
21. **[A Primer on Neural Network Models for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/goldberg-2015-primer-neural-network-models-natural/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Yoav Goldberg*2015 · 1,303 citations*
22. **[Adversarial NLI: A New Benchmark for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/nie-2020-adversarial-nli-new-benchmark-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Nie, Adina Williams, Emily Dinan, et al.*2020 · 1,296 citations*
23. **[Neural Responding Machine for Short-Text Conversation](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,257 citations*
24. [**Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps arXiv:1312.6034**Karen Simonyan, Andrea Vedaldi, Andrew Zisserman*2013 · 1,210 citations*](https://md.research.elamur.ai/free/en/papers/simonyan-2013-deep-inside-convolutional-networks-visualising/)
25. **[Modeling Context in Referring Expressions](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,203 citations*
26. **[EIE: Efficient Inference Engine on Compressed Deep Neural Network](https://md.research.elamur.ai/free/en/papers/han-2016-eie-efficient-inference-engine-compressed/) [ACM/IEEE International Symposium on Computer Architecture (ISCA)](https://md.research.elamur.ai/free/en/venues/acm-ieee-international-symposium-on-computer-architecture-isca/)**Song Han, Xingyu Liu, Huizi Mao, et al.*2016 · 1,193 citations*
27. [**Exact solutions to the nonlinear dynamics of learning in deep linear neural networks arXiv:1312.6120**Andrew M. Saxe, James L. McClelland, Surya Ganguli*2013 · 1,027 citations*](https://md.research.elamur.ai/free/en/papers/saxe-2013-exact-solutions-nonlinear-dynamics-learning/)
28. [**BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain arXiv:1708.06733**Tianyu Gu, Brendan Dolan-Gavitt, Siddharth Garg*2017 · 1,024 citations*](https://md.research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/)
29. [**Visualizing and Understanding Recurrent Networks arXiv:1506.02078**Andrej Karpathy, Justin Johnson, Li Fei-Fei*2015 · 954 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2015-visualizing-understanding-recurrent-networks/)
30. **[Using the Output Embedding to Improve Language Models](https://md.research.elamur.ai/free/en/papers/press-2017-output-embedding-improve-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ofir Press, Lior Wolf*2017 · 909 citations*
31. [**Transition-Based Dependency Parsing with Stack Long Short-Term Memory**Chris Dyer, Miguel Ballesteros, Wang Ling, et al.*2015 · 868 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2015-transition-based-dependency-parsing-stack/)
32. [**Reasoning about Entailment with Neural Attention arXiv:1509.06664**Tim Rocktaschel, Edward Grefenstette, Karl Moritz Hermann, et al.*2015 · 802 citations*](https://md.research.elamur.ai/free/en/papers/rocktaschel-2015-reasoning-about-entailment-neural-attention/)
33. [**Visualizing and Understanding Convolutional Networks arXiv:1311.2901**Matthew D Zeiler, Rob Fergus*2013 · 771 citations*](https://md.research.elamur.ai/free/en/papers/zeiler-2013-visualizing-understanding-convolutional-networks/)
34. [**The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations arXiv:1511.02301**Felix Hill, Antoine Bordes, Sumit Chopra, et al.*2015 · 708 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-goldilocks-principle-reading-children-s/)
35. [**Efficient Neural Architecture Search via Parameter Sharing arXiv:1802.03268**Hieu Pham, Melody Y. Guan, Barret Zoph, et al.*2018 · 699 citations*](https://md.research.elamur.ai/free/en/papers/pham-2018-efficient-neural-architecture-search-parameter/)
36. [**Highway Networks arXiv:1505.00387**Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber*2015 · 680 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2015-highway-networks/)
37. [**Regularizing and Optimizing LSTM Language Models arXiv:1708.02182**Stephen Merity, Nitish Shirish Keskar, Richard Socher*2017 · 633 citations*](https://md.research.elamur.ai/free/en/papers/merity-2017-regularizing-optimizing-lstm-language-models/)
38. **[Transformation Networks for Target-Oriented Sentiment Classification](https://md.research.elamur.ai/free/en/papers/li-2018-transformation-networks-target-oriented-sentiment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Li, Lidong Bing, Wai Lam, et al.*2018 · 600 citations*
39. [**QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension arXiv:1804.09541**Adams Wei Yu, David Dohan, Minh-Thang Luong, et al.*2018 · 597 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-qanet-combining-local-convolution-global/)
40. **[Massive Exploration of Neural Machine Translation Architectures](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Denny Britz, Anna Goldie, Minh-Thang Luong, et al.*2017 · 574 citations*
41. **[Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement](https://md.research.elamur.ai/free/en/papers/lee-2018-deterministic-non-autoregressive-neural-sequence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jason Lee, Elman Mansimov, Kyunghyun Cho*2018 · 568 citations*
42. **[The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chen-2018-best-both-worlds-combining-recent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mia Xu Chen, Orhan Firat, Ankur Bapna, et al.*2018 · 559 citations*
43. [**The Natural Language Decathlon: Multitask Learning as Question Answering arXiv:1806.08730**Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.*2018 · 545 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2018-natural-language-decathlon-multitask-learning/)
44. [**Learning Structured Sparsity in Deep Neural Networks arXiv:1608.03665**Wei Wen, Chunpeng Wu, Yandan Wang, et al.*2016 · 530 citations*](https://md.research.elamur.ai/free/en/papers/wen-2016-learning-structured-sparsity-deep-neural/)
45. [**Deep Learning Scaling is Predictable, Empirically arXiv:1712.00409**Joel Hestness, Sharan Narang, Newsha Ardalani, et al.*2017 · 518 citations*](https://md.research.elamur.ai/free/en/papers/hestness-2017-deep-learning-scaling-predictable-empirically/)
46. [**Learned in Translation: Contextualized Word Vectors arXiv:1708.00107**Bryan McCann, James Bradbury, Caiming Xiong, et al.*2017 · 512 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2017-learned-translation-contextualized-word-vectors/)
47. [**Regularizing Neural Networks by Penalizing Confident Output Distributions arXiv:1701.06548**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 496 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
48. [**Action-Conditional Video Prediction using Deep Networks in Atari Games arXiv:1507.08750**Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, et al.*2015 · 467 citations*](https://md.research.elamur.ai/free/en/papers/oh-2015-action-conditional-video-prediction-using/)
49. [**Adversarial Training Methods for Semi-Supervised Text Classification arXiv:1605.07725**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 433 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
50. [**Deep Learning: A Critical Appraisal arXiv:1801.00631**Gary Marcus*2018 · 417 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2018-deep-learning-critical-appraisal/)
51. [**Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling arXiv:1611.01462**Hakan Inan, Khashayar Khosravi, Richard Socher*2016 · 414 citations*](https://md.research.elamur.ai/free/en/papers/inan-2016-tying-word-vectors-word-classifiers/)
52. **[Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs](https://md.research.elamur.ai/free/en/papers/ballesteros-2015-improved-transition-based-parsing-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miguel Ballesteros, Chris Dyer, Noah A. Smith*2015 · 403 citations*
53. [**Representation Learning: A Review and New Perspectives arXiv:1206.5538**Yoshua Bengio, Aaron Courville, Pascal Vincent*2012 · 383 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/)
54. **[An Analysis of Encoder Representations in Transformer-Based Machine Translation](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Alessandro Raganato, Jörg Tiedemann*2018 · 369 citations*
55. [**Compressive Transformers for Long-Range Sequence Modelling arXiv:1911.05507**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
56. **[On the Practical Computational Power of Finite Precision RNNs for Language Recognition](https://md.research.elamur.ai/free/en/papers/weiss-2018-practical-computational-power-finite-precision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gail Weiss, Yoav Goldberg, Eran Yahav*2018 · 313 citations*
57. [**Finding Function in Form: Compositional Character Models for Open Vocabulary Word Representation arXiv:1508.02096**Wang Ling, Tiago Luis, Luis Marujo, et al.*2015 · 308 citations*](https://md.research.elamur.ai/free/en/papers/ling-2015-finding-function-form-compositional-character/)
58. [**Overcoming Catastrophic Forgetting by Incremental Moment Matching arXiv:1703.08475**Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, et al.*2017 · 298 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-overcoming-catastrophic-forgetting-incremental-moment/)
59. **[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*
60. **[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*
61. [**Hierarchical Multiscale Recurrent Neural Networks arXiv:1609.01704**Junyoung Chung, Sungjin Ahn, Yoshua Bengio*2016 · 288 citations*](https://md.research.elamur.ai/free/en/papers/chung-2016-hierarchical-multiscale-recurrent-neural-networks/)
62. [**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/)
63. **[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*
64. **[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*
65. [**Transformers learn in-context by gradient descent arXiv:2212.07677**Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, et al.*2022 · 247 citations*](https://md.research.elamur.ai/free/en/papers/oswald-2022-transformers-learn-context-gradient-descent/)
66. [**CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service arXiv:1805.01217 · Artif. Intell. Law 27 (2019) 117-139**Marco Lippi, Przemyslaw Palka, Giuseppe Contissa, et al.*2018 · 246 citations*](https://md.research.elamur.ai/free/en/papers/lippi-2018-claudette-automated-detector-potentially-unfair/)
67. [**What learning algorithm is in-context learning? Investigations with linear models arXiv:2211.15661**Ekin Akyürek, Dale Schuurmans, Jacob Andreas, et al.*2022 · 236 citations*](https://md.research.elamur.ai/free/en/papers/akyurek-2022-learning-algorithm-context-learning-investigations/)
68. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents arXiv:2407.16741**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 221 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
69. **[Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking](https://md.research.elamur.ai/free/en/papers/wen-2015-stochastic-language-generation-dialogue-recurrent/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Tsung-Hsien Wen, Milica Gašić, Dongho Kim, et al.*2015 · 216 citations*
70. **[Morphological Inflection Generation with Hard Monotonic Attention](https://md.research.elamur.ai/free/en/papers/aharoni-2017-morphological-inflection-generation-hard-monotonic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roee Aharoni, Yoav Goldberg*2017 · 211 citations*
71. **[Nematus: a Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rico Sennrich, Orhan Firat, Kyunghyun Cho, et al.*2017 · 206 citations*
72. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
73. [**Improving Neural Language Models with a Continuous Cache arXiv:1612.04426**Edouard Grave, Armand Joulin, Nicolas Usunier*2016 · 179 citations*](https://md.research.elamur.ai/free/en/papers/grave-2016-improving-neural-language-models-continuous/)
74. **[Data Augmentation via Dependency Tree Morphing for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/sahin-2018-data-augmentation-dependency-tree-morphing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gözde Gül Şahin, Mark Steedman*2018 · 171 citations*
75. **[Humor Detection: A Transformer Gets the Last Laugh](https://md.research.elamur.ai/free/en/papers/weller-2019-humor-detection-transformer-gets-last/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orion Weller, Kevin Seppi*2019 · 165 citations*
76. [**Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge arXiv:2410.02736**Jiayi Ye, Yanbo Wang, Yue Huang, et al.*2024 · 148 citations*](https://md.research.elamur.ai/free/en/papers/ye-2024-justice-prejudice-quantifying-biases-llm/)
77. [**Recurrent Highway Networks arXiv:1607.03474**Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnik, et al.*2016 · 147 citations*](https://md.research.elamur.ai/free/en/papers/zilly-2016-recurrent-highway-networks/)
78. **[SGM: Sequence Generation Model for Multi-label Classification](https://md.research.elamur.ai/free/en/papers/yang-2018-sgm-sequence-generation-model-multi/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Pengcheng Yang, Xu Sun, Wei Li, et al.*2018 · 146 citations*
79. **[Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/qin-2017-adversarial-connective-exploiting-networks-implicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lianhui Qin, Zhisong Zhang, Hai Zhao, et al.*2017 · 145 citations*
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