no code implementations • 3 Apr 2024 • Qianqiao Xu, Zhiliang Tian, Hongyan Wu, Zhen Huang, Yiping Song, Feng Liu, Dongsheng Li
In this paper, we propose a multi-agent attacker-disguiser game approach to achieve a weak defense mechanism that allows the large model to both safely reply to the attacker and hide the defense intent.
no code implementations • 26 Feb 2024 • Yiping Song, Juhua Zhang, Zhiliang Tian, Yuxin Yang, Minlie Huang, Dongsheng Li
As sufficient data are not always publically accessible for model training, researchers exploit limited data with advanced learning algorithms or expand the dataset via data augmentation (DA).
no code implementations • ACL 2022 • Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang
Building models of natural language processing (NLP) is challenging in low-resource scenarios where only limited data are available.
no code implementations • 5 Dec 2021 • Zheng Xie, Xiaojing Zuo, Yiping Song
Embedding scale-free networks to hyperbolic spaces offer an exciting alternative but incurs distortions when embedding assortative networks with latent geometries not hyperbolic.
no code implementations • 21 May 2021 • Zhiliang Tian, Wei Bi, Zihan Zhang, Dongkyu Lee, Yiping Song, Nevin L. Zhang
The task requires models to generate personalized responses for a speaker given a few conversations from the speaker and a social network.
no code implementations • 24 May 2020 • Zequn Liu, Ruiyi Zhang, Yiping Song, Wei Ju, Ming Zhang
Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning method, is successfully employed in NLP applications including few-shot text classification and multi-domain low-resource language generation.
no code implementations • ACL 2020 • Zhiliang Tian, Wei Bi, Dongkyu Lee, Lanqing Xue, Yiping Song, Xiaojiang Liu, Nevin L. Zhang
In previous work, the external document is utilized by (1) creating a context-aware document memory that integrates information from the document and the conversational context, and then (2) generating responses referring to the memory.
no code implementations • 11 Apr 2020 • Lu-chen Liu, Zequn Liu, Haoxian Wu, Zichang Wang, Jianhao Shen, Yiping Song, Ming Zhang
Mortality prediction of diverse rare diseases using electronic health record (EHR) data is a crucial task for intelligent healthcare.
1 code implementation • ACL 2020 • Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang
Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems.
no code implementations • ICLR 2018 • Yiping Song, Rui Yan, Cheng-Te Li, Jian-Yun Nie, Ming Zhang, Dongyan Zhao
Human-computer conversation systems have attracted much attention in Natural Language Processing.
no code implementations • IJCNLP 2017 • Yiping Song, Zhiliang Tian, Dongyan Zhao, Ming Zhang, Rui Yan
However, traditional seq2seq suffer from a severe weakness: during beam search decoding, they tend to rank universal replies at the top of the candidate list, resulting in the lack of diversity among candidate replies.
no code implementations • ACL 2017 • Zhiliang Tian, Rui Yan, Lili Mou, Yiping Song, Yansong Feng, Dongyan Zhao
Generative conversational systems are attracting increasing attention in natural language processing (NLP).
2 code implementations • 23 Oct 2016 • Yiping Song, Rui Yan, Xiang Li, Dongyan Zhao, Ming Zhang
In this paper, we propose a novel ensemble of retrieval-based and generation-based dialog systems in the open domain.
no code implementations • 13 Oct 2016 • Yiping Song, Lili Mou, Rui Yan, Li Yi, Zinan Zhu, Xiaohua Hu, Ming Zhang
In human-computer conversation systems, the context of a user-issued utterance is particularly important because it provides useful background information of the conversation.
no code implementations • COLING 2016 • Lili Mou, Yiping Song, Rui Yan, Ge Li, Lu Zhang, Zhi Jin
Using neural networks to generate replies in human-computer dialogue systems is attracting increasing attention over the past few years.