Bi-directional Gated Memory Networks for Answer Selection
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Wei Wu | Houfeng Wang | Sujian Li | Houfeng Wang | Wei Wu | Sujian Li
[1] Richard Socher,et al. Dynamic Coattention Networks For Question Answering , 2016, ICLR.
[2] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[3] Man Lan,et al. ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment , 2014, *SEMEVAL.
[4] Zhifang Sui,et al. Recognizing Textual Entailment via Multi-task Knowledge Assisted LSTM , 2016, CCL.
[5] Ming-Wei Chang,et al. Question Answering Using Enhanced Lexical Semantic Models , 2013, ACL.
[6] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[7] Richard Socher,et al. Ask Me Anything: Dynamic Memory Networks for Natural Language Processing , 2015, ICML.
[8] Alice Lai,et al. Illinois-LH: A Denotational and Distributional Approach to Semantics , 2014, *SEMEVAL.
[9] Noah A. Smith,et al. What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA , 2007, EMNLP.
[10] Bowen Zhou,et al. Applying deep learning to answer selection: A study and an open task , 2015, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).
[11] Alessandro Moschitti,et al. Automatic Feature Engineering for Answer Selection and Extraction , 2013, EMNLP.
[12] Xiaolong Wang,et al. Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering , 2015, ACL.
[13] Ali Farhadi,et al. Bidirectional Attention Flow for Machine Comprehension , 2016, ICLR.
[14] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[15] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[16] Rob Fergus,et al. Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[17] Houfeng Wang,et al. Attentive Interactive Neural Networks for Answer Selection in Community Question Answering , 2017, AAAI.
[18] Phil Blunsom,et al. Reasoning about Entailment with Neural Attention , 2015, ICLR.
[19] Quan Hung Tran,et al. JAIST: Combining multiple features for Answer Selection in Community Question Answering , 2015, *SEMEVAL.
[20] Steven Bird,et al. NLTK: The Natural Language Toolkit , 2002, ACL.
[21] Katrin Erk,et al. Representing Meaning with a Combination of Logical Form and Vectors , 2015, ArXiv.
[22] Phil Blunsom,et al. Teaching Machines to Read and Comprehend , 2015, NIPS.
[23] Christopher Potts,et al. A large annotated corpus for learning natural language inference , 2015, EMNLP.
[24] Preslav Nakov,et al. SemEval-2015 Task 3: Answer Selection in Community Question Answering , 2015, *SEMEVAL.
[25] Jason Weston,et al. End-To-End Memory Networks , 2015, NIPS.
[26] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[27] Bowen Zhou,et al. LSTM-based Deep Learning Models for non-factoid answer selection , 2015, ArXiv.
[28] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[29] Zhoujun Li,et al. Knowledge Enhanced Hybrid Neural Network for Text Matching , 2018, AAAI.
[30] Jason Weston,et al. A Neural Attention Model for Abstractive Sentence Summarization , 2015, EMNLP.