30 citations · 108 across the 48 of their papers we have counts for
6 papers · 1 filter
Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction
Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan +5
Joint entity and relation extraction aims to extract relation triplets from plain text directly. Prior work leverages Sequence-to-Sequence (Seq2Seq) models for triplet sequence gen…
Reverse Operation based Data Augmentation for Solving Math Word Problems
Qianying Liu, Wenyu Guan, Sujian Li +3
Automatically solving math word problems is a critical task in the field of natural language processing. Recent models have reached their performance bottleneck and require more hi…
Predicting Event Time by Classifying Sub-Level Temporal Relations Induced from a Unified Representation of Time Anchors
Fei Cheng, Yusuke Miyao
Extracting event time from news articles is a challenging but attractive task. In contrast to the most existing pair-wised temporal link annotation, Reimers et al.(2016) proposed t…
A System for Worldwide COVID-19 Information Aggregation
Akiko Aizawa, Frederic Bergeron, Junjie Chen +26
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhil…
Adversarial Training for Commonsense Inference
Lis Pereira, Xiaodong Liu, Fei Cheng +2
We propose an AdversariaL training algorithm for commonsense InferenCE (ALICE). We apply small perturbations to word embeddings and minimize the resultant adversarial risk to regul…
Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation
Haiyue Song, Raj Dabre, Zhuoyuan Mao +3
Sequence-to-sequence (S2S) pre-training using large monolingual data is known to improve performance for various S2S NLP tasks in low-resource settings. However, large monolingual…