nlp qa projectNatural Language Processing Question Answering Final Project
Stars: ✭ 61 (+90.63%)
gonnp📉Deep learning from scratch using Go. Specializes in natural language processing
Stars: ✭ 26 (-18.75%)
tg2021taskParticipant Kit for the TextGraphs-15 Shared Task on Explanation Regeneration
Stars: ✭ 18 (-43.75%)
unsupervised-qaTemplate-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering
Stars: ✭ 47 (+46.88%)
GraphDBLPa Graph-based instance of DBLP
Stars: ✭ 33 (+3.13%)
textaugmentTextAugment: Text Augmentation Library
Stars: ✭ 280 (+775%)
grad-cam-textImplementation of Grad-CAM for text.
Stars: ✭ 37 (+15.63%)
navecCompact high quality word embeddings for Russian language
Stars: ✭ 118 (+268.75%)
FinBERT-QAFinancial Domain Question Answering with pre-trained BERT Language Model
Stars: ✭ 70 (+118.75%)
game2vecTensorFlow implementation of word2vec applied on https://www.kaggle.com/tamber/steam-video-games dataset, using both CBOW and Skip-gram.
Stars: ✭ 62 (+93.75%)
meltMELT - Matching EvaLuation Toolkit
Stars: ✭ 37 (+15.63%)
doc2vec-golangdoc2vec , word2vec, implemented by golang. word embedding representation
Stars: ✭ 33 (+3.13%)
obiThe Ontology for Biomedical Investigations
Stars: ✭ 49 (+53.13%)
productqaProduct-Aware Answer Generation in E-Commerce Question-Answering
Stars: ✭ 29 (-9.37%)
DocQNAuthor implementation of "Learning to Search in Long Documents Using Document Structure" (Mor Geva and Jonathan Berant, 2018)
Stars: ✭ 21 (-34.37%)
word2vec-on-wikipediaA pipeline for training word embeddings using word2vec on wikipedia corpus.
Stars: ✭ 68 (+112.5%)
word2vec-pytorchExtremely simple and fast word2vec implementation with Negative Sampling + Sub-sampling
Stars: ✭ 145 (+353.13%)
mrqaCode for EMNLP-IJCNLP 2019 MRQA Workshop Paper: "Domain-agnostic Question-Answering with Adversarial Training"
Stars: ✭ 35 (+9.38%)
sent2vecHow to encode sentences in a high-dimensional vector space, a.k.a., sentence embedding.
Stars: ✭ 99 (+209.38%)
OxigraphSPARQL graph database
Stars: ✭ 252 (+687.5%)
QANetA TensorFlow implementation of "QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension"
Stars: ✭ 31 (-3.12%)
cowlA lightweight C/C++ library for working with Web Ontology Language (OWL) ontologies
Stars: ✭ 18 (-43.75%)
jupyter-langsDocker images of Jupyter Lab for various languages.
Stars: ✭ 21 (-34.37%)
backpropBackprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Stars: ✭ 229 (+615.63%)
edent.telA semantic contact page built around SVG
Stars: ✭ 28 (-12.5%)
rdf-validate-shaclValidate RDF data purely in JavaScript. An implementation of the W3C SHACL specification on top of the RDFJS stack.
Stars: ✭ 61 (+90.63%)
GARCode and resources for papers "Generation-Augmented Retrieval for Open-Domain Question Answering" and "Reader-Guided Passage Reranking for Open-Domain Question Answering", ACL 2021
Stars: ✭ 38 (+18.75%)
teachingTeaching material relevant to KGs
Stars: ✭ 61 (+90.63%)
DVQA datasetDVQA Dataset: A Bar chart question answering dataset presented at CVPR 2018
Stars: ✭ 20 (-37.5%)
lda2vecMixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019
Stars: ✭ 27 (-15.62%)
calamusA JSON-LD Serialization Libary for Python
Stars: ✭ 21 (-34.37%)
fiboThe Financial Industry Business Ontology (FIBO) defines the sets of things that are of interest in financial business applications and the ways that those things can relate to one another. In this way, FIBO can give meaning to any data (e.g., spreadsheets, relational databases, XML documents) that describe the business of finance.
Stars: ✭ 204 (+537.5%)
mcQA🔮 Answering multiple choice questions with Language Models.
Stars: ✭ 23 (-28.12%)
MSMARCOMachine Comprehension Train on MSMARCO with S-NET Extraction Modification
Stars: ✭ 31 (-3.12%)
lodexLinked Open Data EXperiment
Stars: ✭ 43 (+34.38%)
HARCode for WWW2019 paper "A Hierarchical Attention Retrieval Model for Healthcare Question Answering"
Stars: ✭ 22 (-31.25%)
MundaneumA clojure wrapper around WikiData
Stars: ✭ 54 (+68.75%)
word2vizVisualization of semantic similarities in word embeddings.
Stars: ✭ 86 (+168.75%)
cherche📑 Neural Search
Stars: ✭ 196 (+512.5%)
iPerceiveApplying 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
Stars: ✭ 52 (+62.5%)
patrick-wechat⭐️🐟 questionnaire wechat app built with taro, taro-ui and heart. 微信问卷小程序
Stars: ✭ 74 (+131.25%)
marc2bibframe2Convert MARC records to BIBFRAME2 RDF
Stars: ✭ 72 (+125%)
morph-kgcPowerful RDF Knowledge Graph Generation with [R2]RML Mappings
Stars: ✭ 77 (+140.63%)
StargraphStarGraph (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.
Stars: ✭ 24 (-25%)
MLH-QuizzetThis 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.
Stars: ✭ 23 (-28.12%)
FlowQAImplementation of conversational QA model: FlowQA (with slight improvement)
Stars: ✭ 197 (+515.63%)
sbbSemantic Body Browser - a tool for graphically exploring an organism's body.
Stars: ✭ 31 (-3.12%)