hred

Multi-turn dialogue baselines written in PyTorch

HRED VHRED VHCR for Multi-Turn Dialogue Systems

Pytorch implementation of Hierarchical Encoder Decoder Sequence to Sequence Model

A PyTorch implementation of the hierarchical encoder-decoder architecture (HRED) introduced in Sordoni et al (2015). It is a hierarchical encoder-decoder architecture for modeling conversation triples in the MovieTriples dataset. This version of the model is built for the MovieTriples dataset.

The codes of our paper When to Talk: Chatbot Controls the Timing of Talking during Multi-turn Open-domain Dialogue Generation

我的本科毕业设计论文

PyTorch implementation on sequence-to-sequence (seq2seq) model and HRED model

Hierarchical Encoder Decoder for Dialog Modelling