no code implementations • 23 May 2022 • Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Kai Zhang, Daxin Jiang
Large-scale retrieval is to recall relevant documents from a huge collection given a query.
no code implementations • 12 Apr 2022 • Qingfeng Sun, Can Xu, Huang Hu, Yujing Wang, Jian Miao, Xiubo Geng, Yining Chen, Fei Xu, Daxin Jiang
(2) How to cohere with context and preserve the knowledge when generating a stylized response.
1 code implementation • ACL 2022 • Jia-Chen Gu, Chao-Hong Tan, Chongyang Tao, Zhen-Hua Ling, Huang Hu, Xiubo Geng, Daxin Jiang
To address these challenges, we present HeterMPC, a heterogeneous graph-based neural network for response generation in MPCs which models the semantics of utterances and interlocutors simultaneously with two types of nodes in a graph.
1 code implementation • Findings (ACL) 2022 • Chao-Hong Tan, Jia-Chen Gu, Chongyang Tao, Zhen-Hua Ling, Can Xu, Huang Hu, Xiubo Geng, Daxin Jiang
To address the problem, we propose augmenting TExt Generation via Task-specific and Open-world Knowledge (TegTok) in a unified framework.
1 code implementation • ACL 2022 • Yucheng Zhou, Tao Shen, Xiubo Geng, Guodong Long, Daxin Jiang
Generating new events given context with correlated ones plays a crucial role in many event-centric reasoning tasks.
1 code implementation • ACL 2022 • YuFei Wang, Can Xu, Qingfeng Sun, Huang Hu, Chongyang Tao, Xiubo Geng, Daxin Jiang
This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks.
no code implementations • 28 Jan 2022 • Qiyu Wu, Chongyang Tao, Tao Shen, Can Xu, Xiubo Geng, Daxin Jiang
A straightforward solution is resorting to more diverse positives from a multi-augmenting strategy, while an open question remains about how to unsupervisedly learn from the diverse positives but with uneven augmenting qualities in the text field.
no code implementations • ACL 2022 • Qingfeng Sun, Yujing Wang, Can Xu, Kai Zheng, Yaming Yang, Huang Hu, Fei Xu, Jessica Zhang, Xiubo Geng, Daxin Jiang
In such a low-resource setting, we devise a novel conversational agent, Divter, in order to isolate parameters that depend on multimodal dialogues from the entire generation model.
no code implementations • 13 Oct 2021 • Yucheng Zhou, Xiubo Geng, Tao Shen, Guodong Long, Daxin Jiang
Event correlation reasoning infers whether a natural language paragraph containing multiple events conforms to human common sense.
no code implementations • 1 Oct 2021 • Chongyang Tao, Jiazhan Feng, Chang Liu, Juntao Li, Xiubo Geng, Daxin Jiang
For this task, the adoption of pre-trained language models (such as BERT) has led to remarkable progress in a number of benchmarks.
1 code implementation • EMNLP 2021 • Zujie Liang, Huang Hu, Can Xu, Jian Miao, Yingying He, Yining Chen, Xiubo Geng, Fan Liang, Daxin Jiang
Second, only the items mentioned in the training corpus have a chance to be recommended in the conversation.
no code implementations • ACL 2021 • Hao Huang, Xiubo Geng, Jian Pei, Guodong Long, Daxin Jiang
Procedural text understanding aims at tracking the states (e. g., create, move, destroy) and locations of the entities mentioned in a given paragraph.
1 code implementation • ACL 2021 • Jia-Chen Gu, Chongyang Tao, Zhen-Hua Ling, Can Xu, Xiubo Geng, Daxin Jiang
Recently, various neural models for multi-party conversation (MPC) have achieved impressive improvements on a variety of tasks such as addressee recognition, speaker identification and response prediction.
no code implementations • NAACL 2021 • Yucheng Zhou, Xiubo Geng, Tao Shen, Wenqiang Zhang, Daxin Jiang
That is, we can only access training data in a high-resource language, while need to answer multilingual questions without any labeled data in target languages.
1 code implementation • ACL 2021 • Zujie Liang, Huang Hu, Can Xu, Chongyang Tao, Xiubo Geng, Yining Chen, Fan Liang, Daxin Jiang
The retriever aims to retrieve a correlated image to the dialog from an image index, while the visual concept detector extracts rich visual knowledge from the image.
no code implementations • 1 Jan 2021 • Zhuoyu Wei, Wei Ji, Xiubo Geng, Yining Chen, Baihua Chen, Tao Qin, Daxin Jiang
We notice that some real-world QA tasks are more complex, which cannot be solved by end-to-end neural networks or translated to any kind of formal representations.
1 code implementation • EMNLP 2020 • Mucheng Ren, Xiubo Geng, Tao Qin, Heyan Huang, Daxin Jiang
We focus on the task of reasoning over paragraph effects in situation, which requires a model to understand the cause and effect described in a background paragraph, and apply the knowledge to a novel situation.
no code implementations • 28 Sep 2020 • Zhihan Zhang, Xiubo Geng, Tao Qin, Yunfang Wu, Daxin Jiang
In this work, we focus on the task of procedural text understanding, which aims to comprehend such documents and track entities' states and locations during a process.
no code implementations • 28 Feb 2020 • Yuyu Zhang, Ping Nie, Xiubo Geng, Arun Ramamurthy, Le Song, Daxin Jiang
Recent studies on open-domain question answering have achieved prominent performance improvement using pre-trained language models such as BERT.
1 code implementation • IJCNLP 2019 • Tao Shen, Xiubo Geng, Tao Qin, Daya Guo, Duyu Tang, Nan Duan, Guodong Long, Daxin Jiang
We consider the problem of conversational question answering over a large-scale knowledge base.
no code implementations • 6 Sep 2019 • Tao Shen, Xiubo Geng, Tao Qin, Guodong Long, Jing Jiang, Daxin Jiang
These two problems lead to a poorly-trained semantic parsing model.
no code implementations • NeurIPS 2010 • Tao Qin, Xiubo Geng, Tie-Yan Liu
To avoid these limitations, in this paper, we propose a new model, which is defined with a coset-permutation distance, and models the generation of a permutation as a stagewise process.