# Machine Reading Comprehension and Question Answering

## Theses
- [2018 Stanford University] **Neural Reading Comprehension and Beyond**, [[thesis]](https://cs.stanford.edu/~danqi/papers/thesis.pdf), [[copy]](/Documents/Theses/Neural%20Reading%20Comprehension%20and%20Beyond.pdf), [[bibtex]](/Bibtex/Neural%20Reading%20Comprehension%20and%20Beyond.bib), author: [[Danqi Chen]](https://cs.stanford.edu/~danqi/).

## Datasets
- [2013 EMNLP] **MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text**, [[paper]](http://aclweb.org/anthology/D13-1020), [[bibtex]](/Bibtex/MCTest%20-%20A%20Challenge%20Dataset%20for%20the%20Open-Domain%20Machine%20Comprehension%20of%20Text.bib), [[homepage]](https://mattr1.github.io/mctest/), source: [[mcobzarenco/mctest]](https://github.com/mcobzarenco/mctest).
- [2015 NIPS] **CNN/DailyMail: Teaching Machines to Read and Comprehend**, [[paper]](https://papers.nips.cc/paper/5945-teaching-machines-to-read-and-comprehend.pdf), [[bibtex]](/Bibtex/CNN-DailyMail%20-%20Teaching%20Machines%20to%20Read%20and%20Comprehend.bib), [[homepage]](https://cs.nyu.edu/~kcho/DMQA/), sources: [[thomasmesnard/DeepMind-Teaching-Machines-to-Read-and-Comprehend]](https://github.com/thomasmesnard/DeepMind-Teaching-Machines-to-Read-and-Comprehend).
- [2016 EMNLP] **SQuAD 100,000+ Questions for Machine Comprehension of Text**, [[paper]](http://aclweb.org/anthology/D16-1264), [[bibtex]](/Bibtex/SQuAD%20Questions%20for%20Machine%20Comprehension%20of%20Text.bib), [[homepage]](https://rajpurkar.github.io/SQuAD-explorer/).
- [2016 ICLR] **bAbI: Towards AI-Complete Question Answering: a Set of Prerequisite Toy Tasks**, [[paper]](https://arxiv.org/pdf/1502.05698.pdf), [[bibtex]](Towards%20AI-Complete%20Question%20Answering%20-%20a%20Set%20of%20Prerequisite%20Toy%20Tasks.bib), [[homepage]](https://research.fb.com/downloads/babi/), sources: [[facebook/bAbI-tasks]](https://github.com/facebook/bAbI-tasks).
- [2017 EMNLP] **World Knowledge for Reading Comprehension: Rare Entity Prediction with Hierarchical LSTMs Using External Descriptions**, [[paper]](http://aclweb.org/anthology/D17-1086), [[bibtex]](/Bibtex/Rare%20Entity%20Prediction%20with%20Hierarchical%20LSTMs%20Using%20External%20Descriptions.bib), [[homepage]](http://dataset.cs.mcgill.ca/downloads/rare_entity_dataset.html).
- [2017 EMNLP] **RACE: Large-scale ReAding Comprehension Dataset From Examinations**, [[paper]](http://aclweb.org/anthology/D17-1082), [[bibtex]](RACE%20-%20Large-scale%20ReAding%20Comprehension%20Dataset%20From%20Examinations.bib), [[homepage]](http://www.cs.cmu.edu/~glai1/data/race/), sources: [[qizhex/RACE_AR_baselines]](https://github.com/qizhex/RACE_AR_baselines).
- [2017 ACL] **TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension**, [[paper]](http://aclweb.org/anthology/P17-1147), [[bibtex]](/Bibtex/TriviaQA%20-%20A%20Large%20Scale%20Distantly%20Supervised%20Challenge%20Dataset%20for%20Reading%20Comprehension.bib) [[homepage]](http://nlp.cs.washington.edu/triviaqa/), sources: [[mandarjoshi90/triviaqa]](https://github.com/mandarjoshi90/triviaqa).
- [2018 TACL] **QAngaroo: Constructing Datasets for Multi-hop Reading Comprehension Across Documents**, [[paper]](http://aclweb.org/anthology/Q18-1021), [[bibtex]](/Bibtex/Constructing%20Datasets%20for%20Multi-hop%20Reading%20Comprehension%20Across%20Documents.bib), [[homepage]](http://qangaroo.cs.ucl.ac.uk).
- [2018 ACL] **Know What You Don’t Know: Unanswerable Questions for SQuAD**, [[paper]](https://www.aclweb.org/anthology/P18-2124.pdf), [[bibtex]](/Bibtex/Know%20What%20You%20Dont%20Know%20-%20Unanswerable%20Questions%20for%20SQuAD.bib), [[supplementary]](https://www.aclweb.org/anthology/attachments/P18-2124.Notes.pdf), [[homepage]](https://rajpurkar.github.io/SQuAD-explorer/), sources: [[CodaLab Worksheet]](https://worksheets.codalab.org/worksheets/0x9a15a170809f4e2cb7940e1f256dee55/).
- [2018 ICLR] **CLOTH: Large-scale Cloze Test Dataset Designed by Teachers**, [[paper]](https://arxiv.org/pdf/1711.03225.pdf), [[bibtex]](/Bibtex/Large-scale%20Cloze%20Test%20Dataset%20Designed%20by%20Teachers.bib), [[homepage]](http://www.qizhexie.com), sources: [[qizhex/Large-scale-Cloze-Test-Dataset-Designed-by-Teachers]](https://github.com/qizhex/Large-scale-Cloze-Test-Dataset-Designed-by-Teachers).
- [2018 NAACL] **(MultiRC) Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences**, [[paper]](http://aclweb.org/anthology/N18-1023), [[bibtex]](/Bibtex/Looking%20Beyond%20the%20Surface%20-%20A%20Challenge%20Set%20for%20Reading%20Comprehension%20over%20Multiple%20Sentences.bib), [[homepage]](http://cogcomp.org/multirc/), sources: [[CogComp/multirc]](https://github.com/CogComp/multirc/).
- [2018 EMNLP] **HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering**, [[paper]](http://aclweb.org/anthology/D18-1259), [[bibtex]](/Bibtex/HotpotQA%20-%20A%20Dataset%20for%20Diverse%20Explainable%20Multi-hop%20Question%20Answering.bib), [[attachment]](http://anthology.aclweb.org/attachments/D/D18/D18-1259.Attachment.pdf), [[homepage]](https://hotpotqa.github.io), sources: [[hotpotqa/hotpot]](https://github.com/hotpotqa/hotpot).
- [2019 NAACL] **CommonsenseQA: A Question Answering Challenge Targeting**, [[paper]](https://arxiv.org/pdf/1811.00937.pdf), [[bibtex]](/Bibtex/CommonsenseQA.md), [[homepage]](https://www.tau-nlp.org/commonsenseqa), sources: [[jonathanherzig/commonsenseqa]](https://github.com/jonathanherzig/commonsenseqa).
- [2019 EMNLP] **COSMOS QA: Machine Reading Comprehension with Contextual Commonsense Reasoning**, [[paper]](https://www.aclweb.org/anthology/D19-1243.pdf), [[bibtex]](/Bibtex/COSMOS%20QA%20-%20Machine%20Reading%20Comprehension%20with%20Contextual%20Commonsense%20Reasoning.bib), [[homepage]](https://wilburone.github.io/cosmos/).
- [2019 TACL] **Natural Questions: a Benchmark for Question Answering Research**, [[paper]](https://www.mitpressjournals.org/doi/pdf/10.1162/tacl_a_00276), [[bibtex]](/Bibtex/Natural%20Questions.bib.bib), [[homepage]](https://ai.google.com/research/NaturalQuestions), sources: [[google-research-datasets/natural-questions]](https://github.com/google-research-datasets/natural-questions).
- [2020 ACL] **MLQA: Evaluating Cross-lingual Extractive Question Answering**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.653.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.653.bib), sources: [[acebookresearch/MLQA]](https://github.com/facebookresearch/MLQA).
- [2020 ACL] **On the Cross-lingual Transferability of Monolingual Representations**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.421.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.421.bib), sources: [[deepmind/xquad]](https://github.com/deepmind/xquad).
- [2020 TACL] **TYDI QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages**, [[paper]](https://aclanthology.org/2020.tacl-1.30.pdf), [[bibtex]](/Bibtex/TYDI%20QA%20-%20A%20Benchmark%20for%20Information-Seeking%20Question%20Answering%20in%20Typologically%20Diverse%20Languages.bib), [[homepage]](https://ai.google.com/research/tydiqa), sources: [[google-research-datasets/tydiqa]](https://github.com/google-research-datasets/tydiqa).
- [2020 ICML] **XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization**, [[paper]](http://proceedings.mlr.press/v119/hu20b/hu20b.pdf), [[bibtex]](/Bibtex/XTREME%20-%20A%20Massively%20Multilingual%20Multi-task%20Benchmark%20for%20Evaluating%20Cross-lingual%20Generalization.bib), [[supplementary]](http://proceedings.mlr.press/v119/hu20b/hu20b-supp.pdf), [[homepage]](https://sites.research.google/xtreme), sources: [[google-research/xtreme]](https://github.com/google-research/xtreme).
- [2020 ICLR] **ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning**, [[paper]](https://openreview.net/pdf?id=HJgJtT4tvB), [[bibtex]](/Bibtex/ReClor%20-%20A%20Reading%20Comprehension%20Dataset%20Requiring%20Logical%20Reasoning.bib), [[homepage]](http://whyu.me/reclor/), sources: [[yuweihao/reclor]](https://github.com/yuweihao/reclor).
- [2020 IJCAI] **LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning**, [[paper]](https://www.ijcai.org/Proceedings/2020/0501.pdf), [[bibtex]](/Bibtex/LogiQA%20-%20A%20Challenge%20Dataset%20for%20Machine%20Reading%20Comprehension%20with%20Logical%20Reasoning.bib), sources: [[lgw863/LogiQA-dataset]](https://github.com/lgw863/LogiQA-dataset).
- [2020 EMNLP] **TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions**, [[paper]](https://www.aclweb.org/anthology/2020.emnlp-main.88.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.emnlp-main.88.bib), [[homepage]](https://allennlp.org/torque.html).

## Methods
- [2014 NIPS] **Deep Learning for Answer Sentence Selection**, [[paper]](https://arxiv.org/pdf/1412.1632.pdf), [[bibtex]](/Bibtex/Deep%20Learning%20for%20Answer%20Sentence%20Selection.bib), sources: [[brmson/Sentence-selection]](https://github.com/brmson/Sentence-selection).
- [2014 ACL] **Freebase QA: Information Extraction or Semantic Parsing?**, [[paper]](https://www.aclweb.org/anthology/W14-2416.pdf), [[bibtex]](https://www.aclweb.org/anthology/W14-2416.bib).
- [2015 IJCAI] **Convolutional Neural Tensor Network Architecture for Community-based Question Answering**, [[paper]](https://www.ijcai.org/Proceedings/15/Papers/188.pdf), [[bibtex]](/Bibtex/Convolutional%20Neural%20Tensor%20Network%20Architecture%20for%20Community-based%20Question%20Answering.bib), sources: [[GauravBh1010tt/DeepLearn]](https://github.com/GauravBh1010tt/DeepLearn/tree/master/convolution%20neural%20tensor%20network), [[SongRb/Seq2SeqLearning]](https://github.com/SongRb/Seq2SeqLearning).
- [2015 NIPS] **Pointer Networks**, [[paper]](https://arxiv.org/pdf/1506.03134.pdf), [[bibtex]](/Bibtex/Pointer%20Networks.bib), [[blog]](http://fastml.com/introduction-to-pointer-networks/), sources: [[devsisters/pointer-network-tensorflow]](https://github.com/devsisters/pointer-network-tensorflow), [[https://github.com/ikostrikov/TensorFlow-Pointer-Networks]](https://github.com/ikostrikov/TensorFlow-Pointer-Networks), [[keon/pointer-networks]](https://github.com/keon/pointer-networks), [[pemami4911/neural-combinatorial-rl-pytorch]](https://github.com/pemami4911/neural-combinatorial-rl-pytorch), [[shiretzet/PointerNet]](https://github.com/shiretzet/PointerNet).
- [2016 ACL] **Question Answering on Freebase via Relation Extraction and Textual Evidence**, [[paper]](https://www.aclweb.org/anthology/P16-1220.pdf), [[bibtex]](https://www.aclweb.org/anthology/P16-1220.bib), sources: [[syxu828/QuestionAnsweringOverFB]](https://github.com/syxu828/QuestionAnsweringOverFB).
- [2016 EMNLP] **Long Short-Term Memory-Networks for Machine Reading**, [[paper]](https://www.aclweb.org/anthology/D16-1053.pdf), [[bibtex]](https://www.aclweb.org/anthology/D16-1053.bib), sources: [[cheng6076/SNLI-attention]](https://github.com/cheng6076/SNLI-attention), [[vsitzmann/snli-attention-tensorflow]](https://github.com/vsitzmann/snli-attention-tensorflow).
- [2016 ICLR] **LSTM-based Deep Learning Models for Non-factoid Answer Selection**, [[paper]](https://arxiv.org/pdf/1511.04108.pdf), [[bibtex]](/Bibtex/LSTM-based%20Deep%20Learning%20Models%20for%20Non-factoid%20Answer%20Selection.bib), sources: [[Alan-Lee123/answer-selection]](https://github.com/Alan-Lee123/answer-selection), [[tambetm/allenAI]](https://github.com/tambetm/allenAI).
- [2016 ICML] **Ask Me Anything: Dynamic Memory Networks for Natural Language Processing**, [[paper]](http://proceedings.mlr.press/v48/kumar16.pdf), [[bibtex]](/Bibtex/Ask%20Me%20Anything.bib), sources: [[DongjunLee/dmn-tensorflow]](https://github.com/DongjunLee/dmn-tensorflow).
- [2016 ACL] **A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task**, [[paper]](https://www.aclweb.org/anthology/P16-1223.pdf), [[bibtex]](https://www.aclweb.org/anthology/P16-1223.bib), sources: [[danqi/rc-cnn-dailymail]](https://github.com/danqi/rc-cnn-dailymail).
- [2016 ICML] **Dynamic Memory Networks for Visual and Textual Question Answering**, [[paper]](http://proceedings.mlr.press/v48/xiong16.pdf), [[bibtex]](/Bibtex/Dynamic%20Memory%20Networks%20for%20Visual%20and%20Textual%20Question%20Answering.bib), [[blog]](https://yerevann.github.io/2016/02/05/implementing-dynamic-memory-networks/), sources: [[therne/dmn-tensorflow]](https://github.com/therne/dmn-tensorflow), [[barronalex/Dynamic-Memory-Networks-in-TensorFlow]](https://github.com/barronalex/Dynamic-Memory-Networks-in-TensorFlow), [[ethancaballero/Improved-Dynamic-Memory-Networks-DMN-plus]](https://github.com/ethancaballero/Improved-Dynamic-Memory-Networks-DMN-plus), [[dandelin/Dynamic-memory-networks-plus-Pytorch]](https://github.com/dandelin/Dynamic-memory-networks-plus-Pytorch), [[DeepRNN/visual_question_answering]](https://github.com/DeepRNN/visual_question_answering).
- [2017 ICLR] **Query-Reduction Networks for Question Answering**, [[paper]](https://arxiv.org/pdf/1606.04582.pdf), [[bibtex]](/Bibtex/Query-Reduction%20Networks%20for%20Question%20Answering.bib), [[homepage]](http://uwnlp.github.io/qrn/), sources: [[uwnlp/qrn]](https://github.com/uwnlp/qrn).
- [2017 ICLR] **Bi-Directional Attention Flow for Machine Comprehension**, [[paper]](https://arxiv.org/pdf/1611.01603.pdf), [[bibtex]](/Bibtex/Bi-Directional%20Attention%20Flow%20for%20Machine%20Comprehension.bib), [[homepage]](https://allenai.github.io/bi-att-flow/), [[demo]](http://allgood.cs.washington.edu:1995), sources: [[allenai/bi-att-flow]](https://github.com/allenai/bi-att-flow).
- [2017 KDD] **ReasoNet: Learning to Stop Reading in Machine Comprehension**, [[paper]](https://arxiv.org/pdf/1609.05284.pdf), [[bibtex]](/Bibtex/ReasoNet%20-%20Learning%20to%20Stop%20Reading%20in%20Machine%20Comprehension.bib), source: [[CNTK/Tutorials/CNTK_302_ReasoNet]](https://github.com/Microsoft/CNTK/blob/penhe/reasonet_tutorial/Tutorials/CNTK_302_ReasoNet.ipynb).
- [2017 ACL] **Learning to Skim Text**, [[paper]](https://www.aclweb.org/anthology/P17-1172.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1172.bib), [[notes]](https://zhuanlan.zhihu.com/p/30555359).
- [2017 ACL] **R-Net: Machine Reading Comprehension with Self-matching Networks** or **Gated Self-Matching Networks for Reading Comprehension and Question Answering**, [[paper]](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/05/r-net.pdf), [[paper]](https://www.aclweb.org/anthology/P17-1018.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1018.bib), [[blog]](http://yerevann.github.io/2017/08/25/challenges-of-reproducing-r-net-neural-network-using-keras/), sources: [[HKUST-KnowComp/R-Net]](https://github.com/HKUST-KnowComp/R-Net), [[YerevaNN/R-NET-in-Keras]](https://github.com/YerevaNN/R-NET-in-Keras), [[minsangkim142/R-net]](https://github.com/minsangkim142/R-net).
- [2017 ICLR] **Machine Comprehension Using Match-LSTM and Answer Pointer**, [[paper]](https://arxiv.org/pdf/1608.07905.pdf), [[bibtex]](/Bibtex/Machine%20Comprehension%20Using%20Match-LSTM%20and%20Answer%20Pointer.bib), sources: [[shuohangwang/SeqMatchSeq]](https://github.com/shuohangwang/SeqMatchSeq), [[MurtyShikhar/Question-Answering]](https://github.com/MurtyShikhar/Question-Answering), [[InnerPeace-Wu/reading_comprehension-cs224n]](https://github.com/InnerPeace-Wu/reading_comprehension-cs224n).
- [2017 EMNLP] **Accurate Supervised and Semi-Supervised Machine Reading for Long Documents**, [[paper]](http://aclweb.org/anthology/D17-1214), [[bibtex]](/Bibtex/Accurate%20Supervised%20and%20Semi-Supervised%20Machine%20Reading%20for%20Long%20Documents.bib).
- [2017 CoNLL] **Making Neural QA as Simple as Possible but not Simpler**, [[paper]](https://www.aclweb.org/anthology/K17-1028.pdf), [[bibtex]](https://www.aclweb.org/anthology/K17-1028.bib), [[homepage]](https://dirkweissenborn.github.io/publications.html), [[github-page]](https://github.com/georgwiese), sources: [[georgwiese/biomedical-qa]](https://github.com/georgwiese/biomedical-qa).
- [2017 EMNLP] **Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension**, [[paper]](https://www.aclweb.org/anthology/D17-1087.pdf), [[bibtex]](https://www.aclweb.org/anthology/D17-1087.bib), sources: [[davidgolub/QuestionGeneration]](https://github.com/davidgolub/QuestionGeneration).
- [2017 ACL] **Attention-over-Attention Neural Networks for Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/P17-1055.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1055.bib), sources: [[OlavHN/attention-over-attention]](https://github.com/OlavHN/attention-over-attention), [[marshmelloX/attention-over-attention]](https://github.com/marshmelloX/attention-over-attention).
- [2017 EMNLP] **Identifying Where to Focus in Reading Comprehension for Neural Question Generation**, [[paper]](https://www.aclweb.org/anthology/D17-1219.pdf), [[bibtex]](/Bibtex/Identifying%20Where%20to%20Focus%20in%20Reading%20Comprehension%20for%20Neural%20Question%20Generation.bib).
- [2017 ACL] **Improved Neural Relation Detection for Knowledge Base Question Answering**, [[paper]](https://www.aclweb.org/anthology/P17-1053.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1053.bib).
- [2017 ACL] **An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge**, [[paper]](https://www.aclweb.org/anthology/P17-1021.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1021.bib), [[homepage]](http://www.nlpr.ia.ac.cn/cip/~liukang/index.html), [[blog]](http://blog.csdn.net/LAW_130625/article/details/78484866).
- [2017 EMNLP] **Learning what to read: Focused machine reading**, [[paper]](http://aclweb.org/anthology/D17-1313), [[bibtex]](/Bibtex/Learning%20what%20to%20read%20-%20Focused%20machine%20reading.bib).
- [2017 ACL] **Reading Wikipedia to Answer Open-Domain Questions**, [[paper]](https://www.aclweb.org/anthology/P17-1171.pdf), [[bibtex]](https://www.aclweb.org/anthology/P17-1171.bib), sources: [[facebookresearch/DrQA]](https://github.com/facebookresearch/DrQA), [[hitvoice/DrQA]](https://github.com/hitvoice/DrQA).
- [2017 CoNLL] **Zero-Shot Relation Extraction via Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/K17-1034.pdf), [[bibtex]](https://www.aclweb.org/anthology/K17-1034.bib), sources: [[omerlevy/bidaf_no_answer]](https://bitbucket.org/omerlevy/bidaf_no_answer/src/default/), [[zhuzhicai/SQuAD2.0-Baseline-Test-with-BiDAF-No-Answer]](https://github.com/zhuzhicai/SQuAD2.0-Baseline-Test-with-BiDAF-No-Answer).
- [2017 AAAI] **Cross Temporal Recurrent Networks for Ranking Question Answer Pairs**, [[paper]](https://oar.a-star.edu.sg/jspui/bitstream/123456789/2406/3/16632-76869-1-PB.pdf), [[bibtex]](/Bibtex/Cross%20Temporal%20Recurrent%20Networks%20for%20Ranking%20Question%20Answer%20Pairs.bib).
- [2018 ICLR] **MaskGAN: Better Text Generation via Filling in the `______`**, [[paper]](https://arxiv.org/pdf/1801.07736.pdf), [[bibtex]](/Bibtex/MaskGAN.bib).
- [2018 AAAI] **Multi-attention Recurrent Network for Human Communication Comprehension**, [[paper]](https://arxiv.org/pdf/1802.00923.pdf), [[bibtex]](/Bibtex/Multi-attention%20Recurrent%20Network%20for%20Human%20Communication%20Comprehension.bib).
- [2018 IEEE Access] **An Attention-Based Word-Level Interaction Model for Knowledge Base Relation Detection**, [[paper]](https://arxiv.org/pdf/1801.09893.pdf), [[bibtex]](/Bibtex/An%20Attention-Based%20Word-Level%20Interaction%20Model%20for%20Knowledge%20Base%20Relation%20Detection.bib).
- [2018 ICLR] **FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension**, [[paper]](https://arxiv.org/pdf/1711.07341.pdf), [[bibtex]](/Bibtex/FusionNet.bib), sources: [[exe1023/FusionNet]](https://github.com/exe1023/FusionNet), [[momohuang/FusionNet-NLI]](https://github.com/momohuang/FusionNet-NLI).
- [2018 NAACL] **Contextualized Word Representations for Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/N18-2088.pdf), [[bibtex]](https://www.aclweb.org/anthology/N18-2088.bib), sources: [[shimisalant/CWR]](https://github.com/shimisalant/CWR).
- [2018 NAACL] **Supervised and Unsupervised Transfer Learning for Question Answering**, [[paper]](https://www.aclweb.org/anthology/N18-1143.pdf), [[bibtex]](https://www.aclweb.org/anthology/N18-1143.bib).
- [2018 ICLR] **QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension** or **Fast and Accurate Reading Comprehension by Combining Self-Attention and Convolution**, [[paper]](https://openreview.net/pdf?id=B14TlG-RW), [[bibtex]](/Bibtex/QANet.bib), sources: [[hengruo/QANet-pytorch]](https://github.com/hengruo/QANet-pytorch), [[NLPLearn/QANet]](https://github.com/NLPLearn/QANet).
- [2018 ICLR] **Neural Speed Reading via Skim-RNN**, [[paper]](https://openreview.net/pdf?id=Sy-dQG-Rb), [[bibtex]](/Bibtex/Neural%20Speed%20Reading%20via%20Skim-RNN.bib), sources: [[schelotto/Neural_Speed_Reading_via_Skim-RNN_PyTorch]](https://github.com/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]](https://www.aclweb.org/anthology/S18-1120.pdf), [[bibtex]](https://www.aclweb.org/anthology/S18-1120.bib), sources: [[intfloat/commonsense-rc]](https://github.com/intfloat/commonsense-rc).
- [2018 ACL] **Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge**, [[paper]](https://www.aclweb.org/anthology/P18-1076.pdf), [[bibtex]](https://www.aclweb.org/anthology/P18-1076.bib).
- [2018 ACL] **Stochastic Answer Networks for Machine Reading Comprehension**, [[paper]](http://aclweb.org/anthology/P18-1157), [[bibtex]](/Bibtex/Stochastic%20Answer%20Networks%20for%20Machine%20Reading%20Comprehension.bib), sources: [[kevinduh/san_mrc]](https://github.com/kevinduh/san_mrc).
- [2018 EMNLP] **Commonsense for Generative Multi-Hop Question Answering Tasks**, [[paper]](https://aclweb.org/anthology/D18-1454), [[bibtex]](/Bibtex/Commonsense%20for%20Generative%20Multi-Hop%20Question%20Answering%20Tasks.bib), sources: [[yicheng-w/CommonSenseMultiHopQA]](https://github.com/yicheng-w/CommonSenseMultiHopQA).
- [2018 NIPS] **Densely Connected Attention Propagation for Reading Comprehension**, [[paper]](https://papers.nips.cc/paper/7739-densely-connected-attention-propagation-for-reading-comprehension.pdf), [[bibtex]](/Bibtex/Densely%20Connected%20Attention%20Propagation%20for%20Reading%20Comprehension.bib), sources: [[vanzytay/NIPS2018_DECAPROP]](https://github.com/vanzytay/NIPS2018_DECAPROP).
- [2018 ArXiv] **Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading**, [[paper]](https://arxiv.org/pdf/1804.10490.pdf), [[bibtex]](/Bibtex/Weaver%20-%20Deep%20Co-Encoding%20of%20Questions%20and%20Documents%20for%20Machine%20Reading.bib).
- [2018 ArXiv] **U-Net: Machine Reading Comprehension with Unanswerable Questions**, [[paper]](https://arxiv.org/pdf/1810.06638.pdf), [[bibtex]](/Bibtex/U-Net.bib), sources: [[FudanNLP/UNet]](https://github.com/FudanNLP/UNet).
- [2018 KDD] **Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction**, [[paper]](https://arxiv.org/pdf/1806.00778.pdf), [[bibtex]](/Bibtex/Multi-Cast%20Attention%20Networks%20for%20Retrieval-based%20Question%20Answering%20and%20Response%20Prediction.bib).
- [2018 ACL] **Simple and Effective Multi-Paragraph Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/P18-1078), [[bibtex]](/Bibtex/Simple%20and%20Effective%20Multi-Paragraph%20Reading%20Comprehension.bib), sources: [[allenai/document-qa]](https://github.com/allenai/document-qa).
- [2018 AAAI] **Reinforced Ranker-Reader for Open-Domain Question Answering**, [[paper]](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16712/16165), [[bibtex]](/Bibtex/Reinforced%20Ranker-Reader%20for%20Open-Domain%20Question%20Answering.bib), sources: [[shuohangwang/mprc]](https://github.com/shuohangwang/mprc).
- [2018 ICLR] **Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering**, [[paper]](https://openreview.net/pdf?id=rJl3yM-Ab), [[bibtex]](/Bibtex/Evidence%20Aggregation%20for%20Answer%20Re-Ranking%20in%20Open-Domain%20Question%20Answering.bib), sources: [[shuohangwang/mprc]](https://github.com/shuohangwang/mprc).
- [2018 NAACL] **The Web as a Knowledge-base for Answering Complex Questions**, [[paper]](https://www.aclweb.org/anthology/N18-1059), [[bibtex]](/Bibtex/The%20Web%20as%20a%20Knowledge-base%20for%20Answering%20Complex%20Questions.bib).
- [2018 EMNLP] **A Nil-Aware Answer Extraction Framework for Question Answering**, [[paper]](https://www.aclweb.org/anthology/D18-1456.pdf), [[bibtex]](https://www.aclweb.org/anthology/D18-1456.bib), sources: [[nusnlp/namanda]](https://github.com/nusnlp/namanda).
- [2018 ICLR] **Ask the Right Questions: Active Question Reformulation with Reinforcement Learning**, [[paper]](https://openreview.net/pdf?id=S1CChZ-CZ), [[bibtex]](/Bibtex/Ask%20the%20Right%20Questions%20-%20Active%20Question%20Reformulation%20with%20Reinforcement%20Learning.bib), sources: [[google/active-qa]](https://github.com/google/active-qa).
- [2019 ACL] **MULTIQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/P19-1485.pdf), [[bibtex]](/Bibtex/MULTIQA%20-%20An%20Empirical%20Investigation%20of%20Generalization%20and%20Transfer%20in%20Reading%20Comprehension.bib), sources: [[alontalmor/MultiQA]](https://github.com/alontalmor/MultiQA).
- [2019 ACL] **Token-level Dynamic Self-Attention Network for Multi-Passage Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/P19-1218.pdf), [[bibtex]](https://www.aclweb.org/anthology/P19-1218.bib).
- [2019 ACL] **Synthetic QA Corpora Generation with Roundtrip Consistency**, [[paper]](https://www.aclweb.org/anthology/P19-1620.pdf), [[bibtex]](https://www.aclweb.org/anthology/P19-1620.bib), [[Supplementary]](https://www.aclweb.org/anthology/attachments/P19-1620.Supplementary.pdf), sources: [[patil-suraj/question_generation]](https://github.com/patil-suraj/question_generation).
- [2019 AAAI] **Read + Verify: Machine Reading Comprehension with Unanswerable Questions**, [[paper]](https://arxiv.org/pdf/1808.05759.pdf), [[bibtex]](/Bibtex/Read%20+%20Verify%20-%20Machine%20Reading%20Comprehension%20with%20Unanswerable%20Questions.bib).
- [2019 ArXiv] **What does BERT Learn from Multiple-Choice Reading Comprehension Datasets?**, [[paper]](https://arxiv.org/pdf/1910.12391.pdf), [[bibtex]](/Bibtex/What%20does%20BERT%20Learn%20from%20Multiple-Choice%20Reading%20Comprehension%20Datasets.bib).
- [2019 ArXiv] **A BERT Baseline for the Natural Questions**, [[paper]](https://arxiv.org/pdf/1901.08634.pdf), [[bibtex]](/Bibtex/A%20BERT%20Baseline%20for%20the%20Natural%20Questions.bib).
- [2019 ArXiv] **Frustratingly Easy Natural Question Answering**, [[paper]](https://arxiv.org/pdf/1909.05286.pdf), [[bibtex]](/Bibtex/Frustratingly%20Easy%20Natural%20Question%20Answering.bib).
- [2019 ArXiv] **How Additional Knowledge can Improve Natural Language Commonsense Question Answering?**, [[paper]](https://arxiv.org/pdf/1909.08855.pdf), [[bibtex]](/Bibtex/How%20Additional%20Knowledge%20can%20Improve%20Natural%20Language%20Commonsense%20Question%20Answering.bib).
- [2019 EMNLP] **Revealing the Importance of Semantic Retrieval for Machine Reading at Scale**, [[paper]](https://www.aclweb.org/anthology/D19-1258.pdf), [[bibtex]](https://www.aclweb.org/anthology/D19-1258.bib), sources: [[easonnie/semanticRetrievalMRS]](https://github.com/easonnie/semanticRetrievalMRS).
- [2019 EMNLP] **Evaluating Question Answering Evaluation**, [[paper]](https://www.aclweb.org/anthology/D19-5817.pdf), [[bibtex]](https://www.aclweb.org/anthology/D19-5817.bib).
- [2020 AAAI] **MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension**, [[paper]](https://arxiv.org/pdf/1910.00458.pdf), [[bibtex]](/Bibtex/MMM%20-%20Multi-stage%20Multi-task%20Learning%20for%20Multi-choice%20Reading%20Comprehension.bib).
- [2020 AAAI] **Unsupervised Domain Adaptation on Reading Comprehension**, [[paper]](https://arxiv.org/pdf/1911.06137.pdf), [[bibtex]](/Bibtex/Unsupervised%20Domain%20Adaptation%20on%20Reading%20Comprehension.bib), sources: [[caoyu1991/CASe]](https://github.com/caoyu1991/CASe).
- [2020 AAAI] **SG-Net: Syntax-Guided Machine Reading Comprehension**, [[paper]](https://arxiv.org/pdf/1908.05147.pdf), [[bibtex]](/Bibtex/SG-Net.bib), sources: [[cooelf/SG-Net]](https://github.com/cooelf/SG-Net).
- [2020 ICLR] **Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention**, [[paper]](https://openreview.net/pdf?id=r1eIiCNYwS), [[bibtex]](/Bibtex/Transformer-XH%20-%20Multi-Evidence%20Reasoning%20with%20Extra%20Hop%20Attention.bib), sources: [[microsoft/Transformer-XH]](https://github.com/microsoft/Transformer-XH).
- [2020 ACL] **Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.654.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.654.bib).
- [2020 ACL] **RikiNet: Reading Wikipedia Pages for Natural Question Answering**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.604.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.604.bib).
- [2020 ACL] **Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.91.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.91.bib), sources: [[lanyunshi/Multi-hopComplexKBQA]](https://github.com/lanyunshi/Multi-hopComplexKBQA).
- [2020 ACL] **Dice Loss for Data-imbalanced NLP Tasks**, [[paper]](https://aclanthology.org/2020.acl-main.45.pdf), [[bibtex]](/Bibtex/Dice%20Loss%20for%20Data-imbalanced%20NLP%20Tasks.bib), sources: [[ShannonAI/dice_loss_for_NLP]](https://github.com/ShannonAI/dice_loss_for_NLP).
- [2020 ACL] **Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension**, [[paper]](https://www.aclweb.org/anthology/2020.acl-main.87.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.acl-main.87.bib).
- [2020 SIGIR] **DC-BERT: Decoupling Question and Document for Efficient Contextual Encoding**, [[paper]](https://arxiv.org/pdf/2002.12591.pdf), [[bibtex]](/Bibtex/DC-BERT%20-%20Decoupling%20Question%20and%20Document%20for%20Efficient%20Contextual%20Encoding.bib), sources: [[gitabtion/DerivativeBertModels]](https://github.com/gitabtion/DerivativeBertModels).
- [2020 EMNLP] **UnifiedQA: Crossing Format Boundaries With a Single QA System**, [[paper]](https://www.aclweb.org/anthology/2020.findings-emnlp.171.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.findings-emnlp.171.bib), sources: [[allenai/unifiedqa]](https://github.com/allenai/unifiedqa).
- [2020 EMNLP] **Zero-Shot Cross-Lingual Transfer with Meta Learning**, [[paper]](https://www.aclweb.org/anthology/2020.emnlp-main.368.pdf), [[bibtex]](https://www.aclweb.org/anthology/2020.emnlp-main.368.bib), sources: [[copenlu/X-MAML]](https://github.com/copenlu/X-MAML).
- [2020 EMNLP] **A Simple and Effective Model for Answering Multi-span Questions**, [[paper]](https://aclanthology.org/2020.emnlp-main.248.pdf), [[bibtex]](/Bibtex/A%20Simple%20and%20Effective%20Model%20for%20Answering%20Multi-span%20Questions.bib), sources: [[eladsegal/tag-based-multi-span-extraction]](https://github.com/eladsegal/tag-based-multi-span-extraction).
- [2020 ArXiv] **Answering Any-hop Open-domain Questions with Iterative Document Reranking**, [[paper]](https://arxiv.org/pdf/2009.07465v2.pdf), [[bibtex]](/Bibtex/Answering%20Any-hop%20Open-domain%20Questions%20with%20Iterative%20Document%20Reranking.bib).
- [2020 ArXiv] **Counterfactual Variable Control for Robust and Interpretable Question Answering**, [[paper]](https://arxiv.org/pdf/2010.05581.pdf), [[bibtex]](/Bibtex/Counterfactual%20Variable%20Control%20for%20Robust%20and%20Interpretable%20Question%20Answering.bib), sources: [[PluviophileYU/CVC-QA]](https://github.com/PluviophileYU/CVC-QA).
- [2021 NAACL] **RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering**, [[paper]](https://aclanthology.org/2021.naacl-main.466.pdf), [[bibtex]](/Bibtex/RocketQA%20-%20An%20Optimized%20Training%20Approach%20to%20Dense%20Passage%20Retrieval%20for%20Open-Domain%20Question%20Answering.bib), sources: [[PaddlePaddle/NAACL2021-RocketQA]](https://github.com/PaddlePaddle/Research/tree/master/NLP/NAACL2021-RocketQA).
- [2021 ACL] **Why Machine Reading Comprehension Models Learn Shortcuts?**, [[paper]](https://aclanthology.org/2021.findings-acl.85.pdf), [[bibtex]](/Bibtex/Why%20Machine%20Reading%20Comprehension%20Models%20Learn%20Shortcuts?.bib), sources: [[luciusssss/why-learn-shortcut]](https://github.com/luciusssss/why-learn-shortcut).
- [2021 ACL] **Syntax-augmented Multilingual BERT for Cross-lingual Transfer**, [[paper]](https://aclanthology.org/2021.acl-long.350.pdf), [[bibtex]](/Bibtex/Syntax-augmented%20Multilingual%20BERT%20for%20Cross-lingual%20Transfer.bib), sources: [[wasiahmad/Syntax-MBERT]](https://github.com/wasiahmad/Syntax-MBERT).
- [2021 ACL] **Consistency Regularization for Cross-Lingual Fine-Tuning**, [[paper]](https://aclanthology.org/2021.acl-long.264.pdf), [[bibtex]](/Bibtex/Consistency%20Regularization%20for%20Cross-Lingual%20Fine-Tuning.bib), sources: [[bozheng-hit/xTune]](https://github.com/bozheng-hit/xTune).