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​DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
Zhang et al.: https://arxiv.org/abs/1911.00536
#ArtificialIntelligence #MachineLearning #Transformer

🔗 DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
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.
Data Science / Machine Learning / AI / Big Data (VK)

Transformer is All You Need: Multimodal Multitask Learning with a Unified Transformer

Ronghang Hu, Amanpreet Singh: https://arxiv.org/abs/2102.10772

#ArtificialIntelligence #DeepLearning #Transformer
Data Science / Machine Learning / AI / Big Data (VK)

The NLP Cookbook: Modern Recipes for Transformer based Deep Learning Architectures
Sushant Singh, Ausif Mahmood: https://arxiv.org/abs/2104.10640
#NLP #Transformer #DeepLearning