AI Bibliography
AI Bibliography |
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Zhang, Y., Sun, S., Galley, M., Chen, Y.-C., Brockett, C., & Gao, X., et al.. (2019). Dialogpt: Large-scale generative pre-training for conversational response generation. arXiv preprint arXiv:1911.00536. |
| Resource type: Journal Article BibTeX citation key: Zhang2019d View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, General Subcategories: AI transfer learning, Autonomous systems, Big data, Decision making, Deep learning, Informatics, Machine learning, Machine recognition, Neural nets, Synthetic intelligence Creators: Brockett, Chen, Dolan, Galley, Gao, Gao, Liu, Sun, Zhang Publisher: Collection: arXiv preprint arXiv:1911.00536 |
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| Abstract |
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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.
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