no code implementations • 17 Dec 2022 • Qike Li, Samir Jamkhande, Pavel Kochetkov, Pai Liu
The randomized assignment maps end users to experiment buckets and balances user characteristics between the groups.
no code implementations • 18 Aug 2022 • Pai Liu, Wenyang Gao, Wenjie Dong, Songfang Huang, Yue Zhang
Open information extraction is an important NLP task that targets extracting structured information from unstructured text without limitations on the relation type or the domain of the text.
1 code implementation • 3 Aug 2022 • Haitao Lin, Lirong Wu, Guojiang Zhao, Pai Liu, Stan Z. Li
While lots of previous works have focused on `goodness-of-fit' of TPP models by maximizing the likelihood, their predictive performance is unsatisfactory, which means the timestamps generated by models are far apart from true observations.
1 code implementation • ACL 2021 • Cunxiang Wang, Pai Liu, Yue Zhang
Recent work has investigated the interesting question using pre-trained language models (PLMs) as knowledge bases for answering open questions.
no code implementations • SEMEVAL 2021 • Zhixiang Chen, Yikun Lei, Pai Liu, Guibing Guo
SemEval task 4 aims to find a proper option from multiple candidates to resolve the task of machine reading comprehension.
no code implementations • SEMEVAL 2020 • Pai Liu
In this paper, we present language model system submitted to SemEval-2020 Task 4 competition: "Commonsense Validation and Explanation".
no code implementations • 13 Jan 2019 • Jingwei Gan, Pai Liu, Rajan K. Chakrabarty
We introduce a generative adversarial network (GAN) model to simulate the 3-dimensional Lagrangian motion of particles trapped in the recirculation zone of a buoyancy-opposed flame.
1 code implementation • 29 Nov 2018 • Pai Liu, Jingwei Gan, Rajan K. Chakrabarty
We introduce a deep learning method to simulate the motion of particles trapped in a chaotic recirculating flame.