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, Lin Ai, Ziwei Gong, Songfang Huang, Zongsheng Li, Ehsan Hoque, Julia Hirschberg, Yue Zhang
Open Information Extraction (OpenIE) represents a crucial NLP task aimed at deriving structured information from unstructured text, unrestricted by relation type or domain.
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.