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MRCPapers
Worth-reading paper list and other awesome resources on Machine Reading Comprehension (MRC) and textual Question Answering (QA). 机器阅读理解与文本问答领域值得一读的论文列表和其他相关资源集合
https://github.com/ZhengZixiang/MRCPapers
Last synced: 5 days ago
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Dataset
- [paper - research-datasets/tydiqa)
- [paper - research-datasets/tydiqa)
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- [paper - research-datasets/tydiqa)
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- [paper - ***C3***
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- [paper - ***MedQuAD***
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- [paper - data)
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- [paper
- [paper - explorer/tree/master/dataset)
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- [paper - research-datasets/tydiqa)
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- [paper - research-datasets/tydiqa)
- [paper - explorer/tree/master/dataset) - ***SQuAD 2.0***
- [paper - research-datasets/tydiqa)
- [paper - research-datasets/tydiqa)
- [paper - research-datasets/tydiqa)
- [paper - research-datasets/tydiqa)
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- [paper - research-datasets/tydiqa)
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Paper
- [paper - att-flow/) - ***BiDAF***
- [paper - Verifier-pytorch) - ***Verfier***
- [paper - ***CogQA***
- [paper - ***DCMN***
- [paper - ***MTMSN***
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- [paper - Net) - ***SG-Net***
- [paper
- [paper - MCQA)
- [paper - ***Retro-Reader***
- [paper - ***DeFormer***
- [paper - Question-Answering)
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- [paper
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- [paper - Verifier-pytorch) - ***Verfier***
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Survey & Review & Tutorial
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Repository & Toolkit
- seriousran / awesome-qa
- AllenAI / allennlp-reading-comprehension - Reading comprehension tookit by the AllenNLP team
- AMontgomerie / question_generator - An NLP system for generating reading comprehension questions
- ankit-ai / BertQA-Attention-on-Steroids
- alsang / BiDAF-pytorch
- BshoterJ / awesome-kgqa - A collection of some materials of knowledge graph question answering
- cdqa-suite / cdQA
- cdqa-suite / cdQA-annotator
- deepset-ai / Haystack
- Facebook Research / ParlAI - A framework for training and evaluating AI models on a variety of openly available dialogue datasets
- efficientqa/retrieval-based-baselines - Tutorials on training and testing retrieval-based models
- IndexFziQ / KMRC-Papers
- krystalan / Multi-hopRC - 多跳阅读理解相关论文
- lcdevelop / ChatBotCourse - 自己动手做聊天机器人教程
- lixinsu / RCZoo
- tangbinh / question-answering
- THUNLP / RCPapers
- xanhho / Reading-Comprehension-Question-Answering-Papers - Survey on Machine Reading Comprehension
- YingZiqiang / PyTorch-MRCToolkit
- ymcui / Chinese-RC-Datasets
- wavewangyue / kbqa - 基于知识库的问答:seq2seq模型实践
- zcgzcgzcg1 / MRC_book - 《机器阅读理解:算法与实践》代码
- songyingxin / BERT-MRC-RACE
- yizhen20133868 / NLP-Conferences-Code
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Blog Post
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English
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Chinese
- 多多笔记 / 开放领域问答梳理系列(1)
- 多多笔记 / 开放领域问答梳理系列(2)
- humdingers / 2020法研杯阅读理解赛道第一名方案
- 知乎问答 / Bert 如何解决长文本问题?
- 多多笔记 / 开放领域问答梳理系列(2)
- 知乎问答 / 机器阅读理解方向有什么值得follow的大佬,网站等等
- changreal / 【总结向】MRC 经典模型与技术
- changreal / 【总结向】从CMRC2019头部排名看中文MRC
- Liberty / 文本太长,Transformer用不了怎么办
- Luke / 机器阅读理解之多答案抽取
- xhsun1997 / 详细介绍有关RACE数据集上经典的机器阅读理解模型
- 科学空间 / 学会提问的BERT:端到端地从篇章中构建问答对
- 科学空间 / “非自回归”也不差:基于MLM的阅读理解问答
- 科学空间 / 万能的seq2seq:基于seq2seq的阅读理解问答
- 平安寿险PAI / 机器阅读理解探索与实践
- 多多笔记 / 开放领域问答梳理系列(2)
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Programming Languages
Sub Categories
Keywords
question-answering
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nlp
7
reading-comprehension
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bert
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machine-reading-comprehension
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natural-language-processing
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awesome-list
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python
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information-retrieval
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gpt-3
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