Libin Shen

Enhanced Story Representation by ConceptNet for Predicting Story Endings

2020

Predicting endings for narrative stories is a grand challenge for machine commonsense reasoning. The task requires ac- curate representation of the story semantics and structured logic knowledge. Pre-trained language models, such as BERT, made progress …

What If Sentence-hood is Hard to Define: A Case Study in Chinese Reading Comprehension

2021

Machine reading comprehension (MRC) is a challenging NLP task for it requires to carefully deal with all linguistic granularities from word, sentence to passage. For extractive MRC, the answer span has been shown mostly determined …

Look Backward and Forward: Self-Knowledge Distillation with Bidirectional Decoder for Neural Machine Translation

2022 · arXiv (Cornell University)

Neural Machine Translation(NMT) models are usually trained via unidirectional decoder which corresponds to optimizing one-step-ahead prediction. However, this kind of unidirectional decoding framework may incline to focus on local structure rather than global coherence. To …