no code implementations • 16 Feb 2018 • Sahisnu Mazumder, Nianzu Ma, Bing Liu
We model the task as an open-world knowledge base completion problem and propose a novel technique called lifelong interactive learning and inference (LiLi) to solve it.
no code implementations • IJCNLP 2015 • Zhiyuan Chen, Nianzu Ma, Bing Liu
This paper proposes a novel lifelong learning (LL) approach to sentiment classification.
no code implementations • 8 Jun 2019 • Hao Wang, Bing Liu, Shuai Wang, Nianzu Ma, Yan Yang
That is, it is possible to improve the NB classifier for a task by improving its model parameters directly by using the retained knowledge from other tasks.
no code implementations • WS 2019 • Sahisnu Mazumder, Bing Liu, Shuai Wang, Nianzu Ma
Dialogue systems are increasingly using knowledge bases (KBs) storing real-world facts to help generate quality responses.
no code implementations • ACL 2020 • Nianzu Ma, Sahisnu Mazumder, Hao Wang, Bing Liu
This paper studies the task of comparative preference classification (CPC).
1 code implementation • 31 Oct 2022 • Nianzu Ma, Sahisnu Mazumder, Alexander Politowicz, Bing Liu, Eric Robertson, Scott Grigsby
Much of the existing work on text novelty detection has been studied at the topic level, i. e., identifying whether the topic of a document or a sentence is novel or not.
1 code implementation • EMNLP 2021 • Nianzu Ma, Alexander Politowicz, Sahisnu Mazumder, Jiahua Chen, Bing Liu, Eric Robertson, Scott Grigsby
This paper proposes to study a fine-grained semantic novelty detection task, which can be illustrated with the following example.
1 code implementation • NeurIPS 2021 • Zixuan Ke, Bing Liu, Nianzu Ma, Hu Xu, Lei Shu
Although several papers have tried to deal with both CF and KT, our experiments show that they suffer from serious CF when the tasks do not have much shared knowledge.
Ranked #1 on Continual Learning on DSC (10 tasks)