1 code implementation • 25 May 2023 • Zi Liang, Pinghui Wang, Ruofei Zhang, Nuo Xu, Lifeng Xing, Shuo Zhang
The drastic increase in language models' parameters has led to a new trend of deploying models in cloud servers, raising growing concerns about private inference for Transformer-based models.
1 code implementation • 25 May 2023 • Zi Liang, Pinghui Wang, Ruofei Zhang, Shuo Zhang, Xiaofan Ye Yi Huang, Junlan Feng
Recent years have seen increasing concerns about the unsafe response generation of large-scale dialogue systems, where agents will learn offensive or biased behaviors from the real-world corpus.
no code implementations • 27 Feb 2023 • Shuo Zhang, Junzhou Zhao, Pinghui Wang, Tianxiang Wang, Zi Liang, Jing Tao, Yi Huang, Junlan Feng
To cope with this problem, we explore to improve multi-action dialog policy learning with explicit and implicit turn-level user feedback received for historical predictions (i. e., logged user feedback) that are cost-efficient to collect and faithful to real-world scenarios.
2 code implementations • 14 Sep 2022 • Yanyun Wang, Dehui Du, Haibo Hu, Zi Liang, YuanHao Liu
Recent years have witnessed the success of recurrent neural network (RNN) models in time series classification (TSC).