DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
At a glance
- Citations
- 104
- References
- 28
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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.
Publication details
- DOI
- 10.48550/arxiv.1911.00536
- OpenAlex
- W3037026762
- Document type
- preprint
- Language
- EN
- Source
- arXiv (Cornell University)
- Last metadata update
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