3 citations · 8 across the 4 of their papers we have counts for
4 papers
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…
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…
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…