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DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation

DialoGPT, a pre-trained transformer model, generates relevant and context-consistent responses in single-turn dialogue settings, outperforming strong baselines.

Year
2019
Venue
arXiv 2019
Authors
9
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arxiv.org/abs/1911.00536v3ARXIV-DEFAULT
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Abstract

We present a large, tunable neural conversational response generation model, DialoGPT (dialogue generative pre-trained transformer). Trained on 147M conversation-like exchanges extracted from Reddit comment chains over a period spanning from 2005 through 2017, DialoGPT extends the Hugging Face PyTorch transformer to attain a performance close to human both in terms of automatic and human evaluation in single-turn dialogue settings. We show that conversational systems that leverage DialoGPT generate more relevant, contentful and context-consistent responses than strong baseline systems. The pre-trained model and training pipeline are publicly released to facilitate research into neural response generation and the development of more intelligent open-domain dialogue systems.

Authors

9