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ldruth's Projects

ambigqa icon ambigqa

AmbigQA: Answering Ambiguous Open-domain Questions

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-as-service icon bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bi-att-flow icon bi-att-flow

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

cmrc2017 icon cmrc2017

The First Evaluation Workshop on Chinese Machine Reading Comprehension (CMRC 2017)

corefqa icon corefqa

Code base for the paper `CorefQA: Coreference Resolution as Query-based Span Prediction`

cqg icon cqg

The codes for ACL2022 paper “CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation

decomp icon decomp

Repository for Decomposed Prompting

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为15个章节,近20万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06

drcd icon drcd

A 30000+ Chinese MRC dataset - Delta Reading Comprehension Dataset

drqa icon drqa

Reading Wikipedia to Answer Open-Domain Questions

flowqa icon flowqa

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

kdconv icon kdconv

KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation

lark icon lark

LAnguage Representations Kit

models icon models

Models and examples built with TensorFlow

mt-dnn icon mt-dnn

Multi-Task Deep Neural Networks for Natural Language Understanding

nlg-eval icon nlg-eval

Evaluation code for various unsupervised automated metrics for Natural Language Generation.

opennmt-tf icon opennmt-tf

Neural machine translation and sequence learning using TensorFlow

peerread icon peerread

Data and code for Kang et al., NAACL 2018's paper titled "A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications"

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