200 Open source projects that are alternatives of or similar to DocQN

A question answering system which utilises machine learning.

No description or website provided.

No description or website provided.

The release of the FreebaseQA data set (NAACL 2019).

A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering

Code and resources for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking for Open-Domain Question Answering", ACL 2021

Instahelp is a Q&A portal website similar to Quora

Code for EMNLP-IJCNLP 2019 MRQA Workshop Paper: "Domain-agnostic Question-Answering with Adversarial Training"

Code for WWW2019 paper "A Hierarchical Attention Retrieval Model for Healthcare Question Answering"

TensorFlow implementation of "Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering," NAACL-18

使用知识图谱，自然语言处理，卷积神经网络等技术，基于python语言，设计了一个数控领域故障诊断专家系统

No description or website provided.

Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index (DenSPI)

Author: Wenhao Yu ([email protected]). EMNLP'20. Transfer Learning for Technical Question Answering.

The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".

The official code of TACL 2021, "Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies".

⭐️🐟 questionnaire wechat app built with taro, taro-ui and heart. 微信问卷小程序

pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

Environment that can be used to evaluate reasoning capabilities of artificial agents

full featured forum, easy to integrate and use.

Noise-Contrastive Estimation for Question Answering with Convolutional Neural Networks (Rao et al. CIKM 2016)

golang 面试集锦

PororoQA, https://arxiv.org/abs/1707.00836

Question Answering as Global Reasoning over Semantic Abstractions (AAAI-18)

Tensorflow/Pytorch implementation of Gated Attention Reader

A TensorFlow implementation of "QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension"

As far as we know, CONVEX is the first unsupervised method for conversational question answering over knowledge graphs. A demo and our benchmark (and more) can be found at

Persian (Farsi) Question Answering Dataset (+ Models)

Calculates the best possible answer for multiple-choice questions using techniques to maximize accuracy without any other outside resources or knowledge.

HEAD-QA: A Healthcare Dataset for Complex Reasoning

No description or website provided.

Original implementation of QA4IE

HBAM: Hierarchical Bi-directional Word Attention Model

Compare six baseline deep learning models on TrecQA

dialogbot, provide search-based dialogue, task-based dialogue and generative dialogue model. 对话机器人，基于问答型对话、任务型对话、聊天型对话等模型实现，支持网络检索问答，领域知识问答，任务引导问答，闲聊问答，开箱即用。

Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering | Python3 | PyTorch | CNNs | Causality | Reasoning | LSTMs | Transformers | Multi-Head Self Attention | Published in IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

Tensorflow implementation of DCN for question answering on the Stanford Question Answering Dataset (SQuAD)

An InformationGain based Question Answering over knowledge Graph system.

Question Answering System using BiDAF Model on SQuAD v2.0

This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.

KitanaQA: Adversarial training and data augmentation for neural question-answering models

📑 Neural Search

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

ODSQA: OPEN-DOMAIN SPOKEN QUESTION ANSWERING DATASET

Experiments with Hugging Face 🔬 🤗

Augmented version of SQUAD 2.0 for Questions

Implementation of conversational QA model: FlowQA (with slight improvement)

Improving Machine Reading Comprehension with General Reading Strategies

NS-CQA: the model of the JWS paper 'Less is More: Data-Efficient Complex Question Answering over Knowledge Bases.' This work has been accepted by JWS 2020.

A dataset of complex questions on semi-structured Wikipedia tables

吹逼我们是认真的

Code and datasets of "Multilingual Extractive Reading Comprehension by Runtime Machine Translation"

Progressively Pretrained Dense Corpus Index for Open-Domain QA and Information Retrieval

[ACL 2020] DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering

[ACL 2020] Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

Machine Comprehension Train on MSMARCO with S-NET Extraction Modification

StarGraph (aka *graph) is a graph database to query large Knowledge Graphs. Playing with Knowledge Graphs can be useful if you are developing AI applications or doing data analysis over complex domains.

Conversational Question Answering on Clinical Text

金融问答平台文本数据采集/爬取，数据源涉及上交所，深交所，全景网及新浪股吧

Ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production.