---
title: "Who cites Eric Huang"
description: "540 papers of the Elamur Research library cite the works of Eric Huang, found in their bibliographies; the most cited first."
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---
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# Who cites Eric Huang

561 citations of their works from 540 papers of our library (of the 140,884 whose bibliographies we read) · 63 with a page here, the most cited first · [← Eric Huang](https://md.research.elamur.ai/free/en/authors/eric-huang/)

1. [**Convolutional Neural Networks for Sentence Classification**Yoon Kim*2014 · 16,218 citations*](https://md.research.elamur.ai/free/en/papers/kim-2014-convolutional-neural-networks-sentence-classification/)
2. [**GloVe: Global Vectors for Word Representation**Jeffrey Pennington, Richard Socher, Christopher Manning*2014 · 5,962 citations*](https://md.research.elamur.ai/free/en/papers/pennington-2014-glove-global-vectors-word-representation/)
3. [**Distributed Representations of Sentences and Documents**Quoc V. Le, Tomas Mikolov*2014 · 5,747 citations*](https://md.research.elamur.ai/free/en/papers/le-2014-distributed-representations-sentences-documents/)
4. [**Efficient Estimation of Word Representations in Vector Space**Tomas Mikolov, Kai Chen, Greg Corrado, et al.*2013 · 3,846 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/)
5. [**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/)
6. [**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/)
7. [**A Structured Self-attentive Sentence Embedding**Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.*2017 · 1,773 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/)
8. [**Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors**Marco Baroni, Georgiana Dinu, Germán Kruszewski*2014 · 1,678 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2014-don-t-count-predict-systematic/)
9. [**SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation**Felix Hill, Roi Reichart, Anna Korhonen*2015 · 1,622 citations*](https://md.research.elamur.ai/free/en/papers/hill-2015-simlex-999-evaluating-semantic-models/)
10. [**Semantic Compositionality through Recursive Matrix-Vector Spaces**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,559 citations*](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
11. [**Improving Word Representations via Global Context and Multiple Word Prototypes**Eric Huang, Richard Socher, Christopher Manning, et al.*2012 · 1,349 citations*](https://md.research.elamur.ai/free/en/papers/huang-2012-improving-word-representations-global-context/)
12. [**Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,341 citations*](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/)
13. [**On the Cross-lingual Transferability of Monolingual Representations**Mikel Artetxe, Sebastian Ruder, Dani Yogatama*2020 · 1,168 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2020-cross-lingual-transferability-monolingual-representations/)
14. [**Baselines and Bigrams: Simple, Good Sentiment and Topic Classification**Sida Wang, Christopher Manning*2012 · 1,116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2012-baselines-bigrams-simple-good-sentiment/)
15. [**Recurrent Attention Network on Memory for Aspect Sentiment Analysis**Peng Chen, Zhongqian Sun, Lidong Bing, et al.*2017 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-recurrent-attention-network-memory-aspect/)
16. [**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/)
17. [**Better Word Representations with Recursive Neural Networks for Morphology**Thang Luong, Richard Socher, Christopher Manning*2013 · 1,017 citations*](https://md.research.elamur.ai/free/en/papers/luong-2013-better-word-representations-recursive-neural/)
18. [**Deep Unordered Composition Rivals Syntactic Methods for Text Classification**Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, et al.*2015 · 914 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2015-deep-unordered-composition-rivals-syntactic/)
19. [**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/)
20. [**A Convolutional Neural Network for Modelling Sentences**Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom*2014 · 824 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2014-convolutional-neural-network-modelling-sentences/)
21. [**Improving Vector Space Word Representations Using Multilingual Correlation**Manaal Faruqui, Chris Dyer*2014 · 819 citations*](https://md.research.elamur.ai/free/en/papers/faruqui-2014-improving-vector-space-word-representations/)
22. [**Linguistic Regularities in Sparse and Explicit Word Representations**Omer Levy, Yoav Goldberg*2014 · 790 citations*](https://md.research.elamur.ai/free/en/papers/levy-2014-linguistic-regularities-sparse-explicit-word/)
23. [**Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths**Yan Xu, Lili Mou, Ge Li, et al.*2015 · 769 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-classifying-relations-long-short-term/)
24. [**Learning Distributed Representations of Sentences from Unlabelled Data**Felix Hill, Kyunghyun Cho, Anna Korhonen*2016 · 756 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-distributed-representations-sentences-unlabelled/)
25. [**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/)
26. [**Semantic Parsing via Paraphrasing**Jonathan Berant, Percy Liang*2014 · 681 citations*](https://md.research.elamur.ai/free/en/papers/berant-2014-semantic-parsing-paraphrasing/)
27. [**Bilingual Word Embeddings for Phrase-Based Machine Translation**Will Y. Zou, Richard Socher, Daniel Cer, et al.*2013 · 680 citations*](https://md.research.elamur.ai/free/en/papers/zou-2013-bilingual-word-embeddings-phrase-based/)
28. [**context2vec: Learning Generic Context Embedding with Bidirectional LSTM**Oren Melamud, Jacob Goldberger, Ido Dagan*2016 · 666 citations*](https://md.research.elamur.ai/free/en/papers/melamud-2016-context2vec-learning-generic-context-embedding/)
29. [**Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space**Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, et al.*2014 · 593 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2014-efficient-non-parametric-estimation-multiple/)
30. [**WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations**Mohammad Taher Pilehvar, Jose Camacho-Collados*2019 · 592 citations*](https://md.research.elamur.ai/free/en/papers/pilehvar-2019-wic-word-context-dataset-evaluating/)
31. [**Leveraging Pre-trained Checkpoints for Sequence Generation Tasks**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 562 citations*](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/)
32. [**Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation**Chao Xing, Dong Wang, Chao Liu, et al.*2015 · 528 citations*](https://md.research.elamur.ai/free/en/papers/xing-2015-normalized-word-embedding-orthogonal-transform/)
33. [**Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis**Wenya Wang, Sinno Jialin Pan, Daniel Dahlmeier, et al.*2016 · 514 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-recursive-neural-conditional-random-fields/)
34. [**Two/Too Simple Adaptations of Word2Vec for Syntax Problems**Wang Ling, Chris Dyer, Alan W. Black, et al.*2015 · 504 citations*](https://md.research.elamur.ai/free/en/papers/ling-2015-two-too-simple-adaptations-word2vec/)
35. [**Inducing Crosslingual Distributed Representations of Words**Alexandre Klementiev, Ivan Titov, Binod Bhattarai*2012 · 501 citations*](https://md.research.elamur.ai/free/en/papers/klementiev-2012-inducing-crosslingual-distributed-representations-words/)
36. [**Bilingual Word Representations with Monolingual Quality in Mind**Thang Luong, Hieu Pham, Christopher D. Manning*2015 · 453 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-bilingual-word-representations-monolingual-quality/)
37. [**Natural Language Inference by Tree-Based Convolution and Heuristic Matching**Lili Mou, Rui Men, Ge Li, et al.*2016 · 425 citations*](https://md.research.elamur.ai/free/en/papers/mou-2016-natural-language-inference-tree-based/)
38. [**Tailoring Continuous Word Representations for Dependency Parsing**Mohit Bansal, Kevin Gimpel, Karen Livescu*2014 · 418 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2014-tailoring-continuous-word-representations-dependency/)
39. [**Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms**Dinghan Shen, Guoyin Wang, Wenlin Wang, et al.*2018 · 383 citations*](https://md.research.elamur.ai/free/en/papers/shen-2018-baseline-needs-more-love-simple/)
40. [**Multilingual Models for Compositional Distributed Semantics**Karl Moritz Hermann, Phil Blunsom*2014 · 375 citations*](https://md.research.elamur.ai/free/en/papers/hermann-2014-multilingual-models-compositional-distributed-semantics/)
41. [**Improving Lexical Embeddings with Semantic Knowledge**Mo Yu, Mark Dredze*2014 · 371 citations*](https://md.research.elamur.ai/free/en/papers/yu-2014-improving-lexical-embeddings-semantic-knowledge/)
42. [**Metaphor Detection with Cross-Lingual Model Transfer**Yulia Tsvetkov, Leonid Boytsov, Anatole Gershman, et al.*2014 · 369 citations*](https://md.research.elamur.ai/free/en/papers/tsvetkov-2014-metaphor-detection-cross-lingual-model/)
43. [**Political Ideology Detection Using Recursive Neural Networks**Mohit Iyyer, Peter Enns, Jordan Boyd-Graber, et al.*2014 · 368 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2014-political-ideology-detection-recursive-neural/)
44. [**A Unified Model for Word Sense Representation and Disambiguation**Xinxiong Chen, Zhiyuan Liu, Maosong Sun*2014 · 358 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-unified-model-word-sense-representation/)
45. [**Fracking Sarcasm using Neural Network**Aniruddha Ghosh, Tony Veale*2016 · 350 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2016-fracking-sarcasm-neural-network/)
46. [**SensEmbed: Learning Sense Embeddings for Word and Relational Similarity**Ignacio Iacobacci, Mohammad Taher Pilehvar, Roberto Navigli*2015 · 348 citations*](https://md.research.elamur.ai/free/en/papers/iacobacci-2015-sensembed-learning-sense-embeddings-word/)
47. [**Learning Semantic Hierarchies via Word Embeddings**Ruiji Fu, Jiang Guo, Bing Qin, et al.*2014 · 327 citations*](https://md.research.elamur.ai/free/en/papers/fu-2014-learning-semantic-hierarchies-word-embeddings/)
48. [**A Comparison of Vector-based Representations for Semantic Composition**William Blacoe, Mirella Lapata*2012 · 320 citations*](https://md.research.elamur.ai/free/en/papers/blacoe-2012-comparison-vector-based-representations-semantic/)
49. [**Representation Learning: A Review and New Perspectives**Yoshua Bengio, Aaron Courville, Pascal Vincent*2012 · 316 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/)
50. [**Learning Joint Multilingual Sentence Representations with Neural Machine Translation**Holger Schwenk, Matthijs Douze*2017 · 295 citations*](https://md.research.elamur.ai/free/en/papers/schwenk-2017-learning-joint-multilingual-sentence-representations/)
51. [**Reasoning With Neural Tensor Networks for Knowledge Base Completion**Richard Socher, Danqi Chen, Christopher D. Manning, et al.*2013 · 254 citations*](https://md.research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/)
52. [**Linear Algebraic Structure of Word Senses, with Applications to Polysemy**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2018 · 247 citations*](https://md.research.elamur.ai/free/en/papers/arora-2018-linear-algebraic-structure-word-senses/)
53. [**Learning to Understand Phrases by Embedding the Dictionary**Felix Hill, Kyunghyun Cho, Anna Korhonen, et al.*2016 · 234 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-understand-phrases-embedding-dictionary/)
54. [**Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution**Sam Wiseman, Alexander M. Rush, Stuart Shieber, et al.*2015 · 209 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2015-learning-anaphoricity-antecedent-ranking-features/)
55. [**A Neural Network Approach to Selectional Preference Acquisition**Van de Cruys, Tim*2014 · 79 citations*](https://md.research.elamur.ai/free/en/papers/cruys-2014-neural-network-approach-selectional-preference/)
56. [**Ontology-Aware Token Embeddings for Prepositional Phrase Attachment**Pradeep Dasigi, Waleed Ammar, Chris Dyer, et al.*2017 · 35 citations*](https://md.research.elamur.ai/free/en/papers/dasigi-2017-ontology-aware-token-embeddings-prepositional/)
57. [**MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)**Enrique Manjavacas Arevalo, Lauren Fonteyn*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/arevalo-2021-macberth-development-evaluation-historically-pre/)
58. [**Large Scale Substitution-based Word Sense Induction**Matan Eyal, Shoval Sadde, Hillel Taub-Tabib, et al.*2022 · 21 citations*](https://md.research.elamur.ai/free/en/papers/eyal-2022-substitution-wsi/)
59. [**The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks**Dominik Schlechtweg, Sachin Yadav, Jonas Kuhn, et al.*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/schlechtweg-2026-lscd-benchmark-testbed-diachronic-word/)
60. [**Probabilistic Modelling of Morphologically Rich Languages**Jan A. Botha*2015 · 4 citations*](https://md.research.elamur.ai/free/en/papers/botha-2015-probabilistic-modelling-morphologically-rich-languages/)
61. [**WordNet under Scrutiny: Dictionary Examples in the Era of Large Language Models**Fatemah Yousef Almeman, Steven Schockaert, Luis Espinosa Anke*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/almeman-2024-wordnet-examples-llm/)
62. [**Prepositional Phrase Attachment over Word Embedding Products**Pranava Swaroop Madhyastha, Xavier Carreras, Ariadna Quattoni*2017 · 1 citation*](https://md.research.elamur.ai/free/en/papers/madhyastha-2017-prepositional-phrase-attachment-over-word/)
63. [**Context-8: A Data Set for Evaluating Context Sensitivity in Machine Translation**Dongyue Wang, Kyo Kageura*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-context-8-data-set-evaluating/)

477 more citing papers of our library have no page here yet.

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