no code implementations • 24 Oct 2023 • Zhiling Zhang, Jie Zhang, Kui Zhang, Wenbo Zhou, Weiming Zhang, Nenghai Yu
To address these concerns, researchers are actively exploring the concept of ``unlearnable examples", by adding imperceptible perturbation to data in the model training stage, which aims to prevent the model from learning discriminate features of the target face.
no code implementations • 23 May 2023 • Siyuan Chen, Mengyue Wu, Kenny Q. Zhu, Kunyao Lan, Zhiling Zhang, Lyuchun Cui
Empowering chatbots in the field of mental health is receiving increasing amount of attention, while there still lacks exploration in developing and evaluating chatbots in psychiatric outpatient scenarios.
1 code implementation • 4 May 2023 • Zhiling Zhang, Mengyue Wu, Kenny Q. Zhu
Controlling chatbot utterance generation with multiple attributes such as personalities, emotions and dialogue acts is a practically useful but under-studied problem.
no code implementations • 23 May 2022 • Zhiling Zhang, Siyuan Chen, Mengyue Wu, Kenny Q. Zhu
Mental disease detection (MDD) from social media has suffered from poor generalizability and interpretability, due to lack of symptom modeling.
1 code implementation • 19 May 2022 • Zhiling Zhang, Siyuan Chen, Mengyue Wu, Kenny Q. Zhu
Depression is a prominent health challenge to the world, and early risk detection (ERD) of depression from online posts can be a promising technique for combating the threat.
1 code implementation • 10 Oct 2021 • Zelin Zhou, Zhiling Zhang, Xuenan Xu, Zeyu Xie, Mengyue Wu, Kenny Q. Zhu
Current metrics are found in poor correlation with human annotations on these datasets.
1 code implementation • 21 Apr 2021 • Zhiling Zhang, Kenny Q. Zhu
Due to the variety of possible user backgrounds and use cases, the information need can be quite diverse but also specific to a detailed topic, while previous works assume generating one CQ per context and the results tend to be generic.
no code implementations • 11 Nov 2019 • Junjie Pan, Xiang Yin, Zhiling Zhang, Shichao Liu, Yang Zhang, Zejun Ma, Yuxuan Wang
In Mandarin text-to-speech (TTS) system, the front-end text processing module significantly influences the intelligibility and naturalness of synthesized speech.