- [2014 NIPS] Deep Learning for Answer Sentence Selection, [paper], sources: [brmson/Sentence-selection].
- [2014 ACL] Freebase QA: Information Extraction or Semantic Parsing?, [paper].
- [2015 IJCAI] Convolutional Neural Tensor Network Architecture for Community-based Question Answering, [paper], [bibtex], sources: [GauravBh1010tt/DeepLearn], [SongRb/Seq2SeqLearning].
- [2015 NIPS] Pointer Networks, [paper], [blog], sources: [devsisters/pointer-network-tensorflow], [https://github.com/ikostrikov/TensorFlow-Pointer-Networks], [keon/pointer-networks], [pemami4911/neural-combinatorial-rl-pytorch], [shiretzet/PointerNet].
- [2016 ACL] Question Answering on Freebase via Relation Extraction and Textual Evidence, [paper], sources: [syxu828/QuestionAnsweringOverFB].
- [2016 EMNLP] Long Short-Term Memory-Networks for Machine Reading, [paper], sources: [cheng6076/SNLI-attention], [vsitzmann/snli-attention-tensorflow].
- [2016 ICLR] LSTM-based Deep Learning Models for Non-factoid Answer Selection, [paper], sources: [Alan-Lee123/answer-selection], [tambetm/allenAI].
- [2016 ICML] Ask Me Anything: Dynamic Memory Networks for Natural Language Processing, [paper], sources: [DongjunLee/dmn-tensorflow].
- [2016 ACL] A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task, [paper], sources: [danqi/rc-cnn-dailymail].
- [2016 ICML] Dynamic Memory Networks for Visual and Textual Question Answering, [paper], [blog], sources: [therne/dmn-tensorflow], [barronalex/Dynamic-Memory-Networks-in-TensorFlow], [ethancaballero/Improved-Dynamic-Memory-Networks-DMN-plus], [dandelin/Dynamic-memory-networks-plus-Pytorch], [DeepRNN/visual_question_answering].
- [2017 ICLR] Query-Reduction Networks for Question Answering, [paper], [homepage], sources: [uwnlp/qrn].
- [2017 ICLR] Bi-Directional Attention Flow for Machine Comprehension, [paper], [homepage], [demo], sources: [allenai/bi-att-flow].
- [2017 KDD] ReasoNet: Learning to Stop Reading in Machine Comprehension, [paper], [bibtex], source: [CNTK/Tutorials/CNTK_302_ReasoNet].
- [2017 ACL] Learning to Skim Text, [paper], [notes].
- [2017 ACL] R-Net: Machine Reading Comprehension with Self-matching Networks, [paper], [blog], sources: [HKUST-KnowComp/R-Net], [YerevaNN/R-NET-in-Keras], [minsangkim142/R-net].
- [2017 ICLR] Machine Comprehension Using Match-LSTM and Answer Pointer, [paper], sources: [shuohangwang/SeqMatchSeq], [MurtyShikhar/Question-Answering], [InnerPeace-Wu/reading_comprehension-cs224n].
- [2017 EMNLP] Accurate Supervised and Semi-Supervised Machine Reading for Long Documents, [paper], [bibtex].
- [2017 ArXiv] Simple and Effective Multi-Paragraph Reading Comprehension, [paper], sources: [allenai/document-qa].
- [2017 CoNLL] Making Neural QA as Simple as Possible but not Simpler, [paper], [homepage], [github-page], sources: [georgwiese/biomedical-qa].
- [2017 EMNLP] Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension, [paper], sources: [davidgolub/QuestionGeneration].
- [2017 ACL] Attention-over-Attention Neural Networks for Reading Comprehension, [paper], sources: [OlavHN/attention-over-attention], [marshmelloX/attention-over-attention].
- [2017 EMNLP] Identifying Where to Focus in Reading Comprehension for Neural Question Generation, [paper], [bibtex].
- [2017 ACL] Improved Neural Relation Detection for Knowledge Base Question Answering, [paper].
- [2017 ACL] An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge, [paper], [homepage], [blog].
- [2017 EMNLP] Learning what to read: Focused machine reading, [paper], [bibtex].
- [2017 ACL] Reading Wikipedia to Answer Open-Domain Questions, [paper], sources: [facebookresearch/DrQA], [hitvoice/DrQA].
- [2018 ICLR] MaskGAN: Better Text Generation via Filling in the
______, [paper]. - [2018 AAAI] Multi-attention Recurrent Network for Human Communication Comprehension, [paper].
- [2018 ArXiv] An Attention-Based Word-Level Interaction Model: Relation Detection for Knowledge Base Question Answering, [paper].
- [2018 ICLR] FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension, [paper], sources: [exe1023/FusionNet], [momohuang/FusionNet-NLI].
- [2018 NAACL] Contextualized Word Representations for Reading Comprehension, [paper], sources: [shimisalant/CWR].
- [2018 ICLR] QANet: Combing Local Convolution with Global Self-Attention for Reading Comprehension, [paper], sources: [hengruo/QANet-pytorch], [NLPLearn/QANet].
- [2018 ICLR] Neural Speed Reading via Skim-RNN, [paper], sources: [schelotto/Neural_Speed_Reading_via_Skim-RNN_PyTorch].
- [2018 SemEval] Yuanfudao at SemEval-2018 Task 11: Three-way Attention and Relational Knowledge for Commonsense Machine Comprehension, [paper], sources: [intfloat/commonsense-rc].
- [2018 ACL] Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge, [paper].
- [2018 ACL] Stochastic Answer Networks for Machine Reading Comprehension, [paper], [bibtex], sources: [kevinduh/san_mrc].