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Although pre-trained language models have remarkably enhanced the generationability of dialogue systems, open-domain Chinese dialogue systems are stilllimited by the dialogue data and the model size compared with English ones. Inthis paper, we propose EVA, a Chinese dialogue system that contains the largestChinese pre-trained dialogue model with 2.8B parameters. To build this model,we collect the largest Chinese dialogue dataset named WDC-Dialogue from variouspublic social media. This dataset contains 1.4B context-response pairs and isused as the pre-training corpus of EVA. Extensive experiments on automatic andhuman evaluation show that EVA outperforms other Chinese pre-trained dialoguemodels especially in the multi-turn interaction of human-bot conversations.

EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training