13 citations · 31 across the 7 of their papers we have counts for
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cs.CL2019★ 13 cited
End-to-End Trainable Non-Collaborative Dialog System
Yu Li, Kun Qian, Weiyan Shi +1
End-to-end task-oriented dialog models have achieved promising performance on collaborative tasks where users willingly coordinate with the system to complete a given task. While i…
cs.CL2019★ 3 cited
How to Build User Simulators to Train RL-based Dialog Systems
Weiyan Shi, Kun Qian, Xuewei Wang +1
User simulators are essential for training reinforcement learning (RL) based dialog models. The performance of the simulator directly impacts the RL policy. However, building a goo…