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Natural Language Processing
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Machine Reading Comprehension
966 directly classified papers
Papers per year
2015: 2
2016: 2
2017: 23
2018: 51
2019: 118
2020: 122
2021: 144
2022: 107
2023: 111
2024: 117
2025: 140
2026: 29
Papers
SG-Net: Syntax-Guided Machine Reading Comprehension
AAAI 2020
NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets
EMNLP 2020
Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension
EMNLP 2020
A Wrong Answer or a Wrong Question? An Intricate Relationship between Question Reformulation and Answer Selection in Conversational Question Answering
EMNLP 2020
A Simple and Effective Model for Answering Multi-span Questions
EMNLP 2020
PolicyQA: A Reading Comprehension Dataset for Privacy Policies
EMNLP 2020
Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It’s complicated!
EMNLP 2020
Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading
EMNLP 2020
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries
EMNLP 2020
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension
EMNLP 2020
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?
EMNLP 2020
ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion
AAAI 2020
Discriminative Sentence Modeling for Story Ending Prediction
AAAI 2020
Answer Generation through Unified Memories over Multiple Passages
IJCAI 2020
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension
EMNLP 2020
Question Answering with Long Multiple-Span Answers
EMNLP 2020
Teaching Machine Comprehension with Compositional Explanations
EMNLP 2020
FQuAD: French Question Answering Dataset
EMNLP 2020
Towards Interpreting BERT for Reading Comprehension Based QA
EMNLP 2020
A Multilingual Reading Comprehension System for more than 100 Languages
COLING 2020
FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection
COLING 2020
Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension
COLING 2020
Bi-directional CognitiveThinking Network for Machine Reading Comprehension
COLING 2020
Robust Machine Reading Comprehension by Learning Soft labels
COLING 2020
Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian
COLING 2020
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