A modular RL library to fine-tune language models to human preferences

📖 Paper reading list in dialogue systems and natural language generation (constantly updating 🤗).

RNNLG is an open source benchmark toolkit for Natural Language Generation (NLG) in spoken dialogue system application domains. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.

NNDial is an open source toolkit for building end-to-end trainable task-oriented dialogue models. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.

This repository contains a new generative model of chatbot based on seq2seq modeling.

A list of recent papers regarding dialogue generation

A Paper List for Open-Domain Dialogue Generation, and related datasets.

🥤🧑🏻‍🚀Code and dataset for our EMNLP 2023 paper - "SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization"

Deep-Reinforcement-Learning-for-Dialogue-Generation-in-tensorflow

Conversational AI tooling & personas built on Cohere's LLMs

This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.

Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

Generating responses with pretrained XLNet and GPT-2 in PyTorch.

The implementation of the paper "Augmenting Neural Response Generation with Context-Aware Topical Attention"

Official repository of the AAAI'2022 paper "GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection"

EMNLP 2021 - CTC: A Unified Framework for Evaluating Natural Language Generation

Code for the paper Code for the paper InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning

Code for ACL 2021 main conference paper "Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances".

A PyTorch Implementation of japanese chatbot using BERT and Transformer's decoder

MoEL: Mixture of Empathetic Listeners