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Natural Language Inference by Tree-Based Convolution and Heuristic Matching
Lili Mou
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Rui Men
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Ge Li
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Yan Xu
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Lu Zhang
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Rui Yan
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Zhi Jin
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Paper Details:
Month: August
Year: 2016
Location: Berlin, Germany
Venue:
ACL |
Citations
URL
An Empirical Evaluation of various Deep Learning Architectures for Bi-Sequence Classification Tasks
Anirban Laha
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Vikas Raykar
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Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition
Lei Sha
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Baobao Chang
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Zhifang Sui
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Sujian Li
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Adopting the Word-Pair-Dependency-Triplets with Individual Comparison for Natural Language Inference
Qianlong Du
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Chengqing Zong
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Keh-Yih Su
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Ensure the Correctness of the Summary: Incorporate Entailment Knowledge into Abstractive Sentence Summarization
Haoran Li
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Junnan Zhu
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Jiajun Zhang
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Chengqing Zong
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Enhancing Sentence Embedding with Generalized Pooling
Qian Chen
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Zhen-Hua Ling
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Xiaodan Zhu
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Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection
Tirthankar Ghosal
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Vignesh Edithal
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Asif Ekbal
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Pushpak Bhattacharyya
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George Tsatsaronis
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Srinivasa Satya Sameer Kumar Chivukula
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Learning Context-Sensitive Convolutional Filters for Text Processing
Dinghan Shen
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Martin Renqiang Min
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Yitong Li
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Lawrence Carin
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Phrase-level Self-Attention Networks for Universal Sentence Encoding
Wei Wu
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Houfeng Wang
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Tianyu Liu
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Shuming Ma
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Neural Tree Indexers for Text Understanding
Tsendsuren Munkhdalai
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Hong Yu
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Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment
Masatoshi Tsuchiya
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams
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Nikita Nangia
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Samuel Bowman
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DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference
Reza Ghaeini
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Sadid A. Hasan
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Vivek Datla
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Joey Liu
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Kathy Lee
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Ashequl Qadir
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Yuan Ling
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Aaditya Prakash
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Xiaoli Fern
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Oladimeji Farri
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On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference
Adam Poliak
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Yonatan Belinkov
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James Glass
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Benjamin Van Durme
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Training a Ranking Function for Open-Domain Question Answering
Phu Mon Htut
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Samuel Bowman
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Kyunghyun Cho
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A Fast Unified Model for Parsing and Sentence Understanding
Samuel R. Bowman
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Jon Gauthier
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Abhinav Rastogi
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Raghav Gupta
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Christopher D. Manning
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Christopher Potts
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Enhanced LSTM for Natural Language Inference
Qian Chen
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Xiaodan Zhu
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Zhen-Hua Ling
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Si Wei
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Hui Jiang
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Diana Inkpen
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Discourse Marker Augmented Network with Reinforcement Learning for Natural Language Inference
Boyuan Pan
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Yazheng Yang
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Zhou Zhao
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Yueting Zhuang
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Deng Cai
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Xiaofei He
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Multi-Granularity Hierarchical Attention Fusion Networks for Reading Comprehension and Question Answering
Wei Wang
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Ming Yan
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Chen Wu
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Neural Natural Language Inference Models Enhanced with External Knowledge
Qian Chen
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Xiaodan Zhu
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Zhen-Hua Ling
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Diana Inkpen
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Si Wei
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Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
Max Glockner
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Vered Shwartz
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Yoav Goldberg
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Do latent tree learning models identify meaningful structure in sentences?
Adina Williams
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Andrew Drozdov
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Samuel R. Bowman
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Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms
Wenpeng Yin
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Hinrich Schütze
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Element-wise Bilinear Interaction for Sentence Matching
Jihun Choi
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Taeuk Kim
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Sang-goo Lee
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Research on attention memory networks as a model for learning natural language inference
Zhuang Liu
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Degen Huang
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Jing Zhang
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Kaiyu Huang
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Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference
Qian Chen
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Xiaodan Zhu
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Zhen-Hua Ling
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Si Wei
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Hui Jiang
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Diana Inkpen
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https://sites.google.com/site/tbcnninference/
http://arxiv.org/abs/1409.5718v1
http://nlp.stanford.edu/software/lex-parser.shtml
http://nlp.stanford.edu/projects/snli/
Field Of Study
Linguistic Trends
Discourse
Embeddings
Task
Language Understanding
Textual Entailment
Information Retrieval
Question Answering
Summarization
Language
English
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