204 citations · 344 across the 21 of their papers we have counts for
8 papers · 1 filter
A BERT-based Dual Embedding Model for Chinese Idiom Prediction
Minghuan Tan, Jing Jiang
Chinese idioms are special fixed phrases usually derived from ancient stories, whose meanings are oftentimes highly idiomatic and non-compositional. The Chinese idiom prediction ta…
Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention
Yang Li, Tao Shen, Guodong Long +3
Wrong labeling problem and long-tail relations are two main challenges caused by distant supervision in relation extraction. Recent works alleviate the wrong labeling by selective…
Counterfactual Variable Control for Robust and Interpretable Question Answering
Sicheng Yu, Yulei Niu, Shuohang Wang +2
Deep neural network based question answering (QA) models are neither robust nor explainable in many cases. For example, a multiple-choice QA model, tested without any input of ques…
Cross-Thought for Sentence Encoder Pre-training
Shuohang Wang, Yuwei Fang, Siqi Sun +4
In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks…
Context Modeling with Evidence Filter for Multiple Choice Question Answering
Sicheng Yu, Hao Zhang, Wei Jing +1
Multiple-Choice Question Answering (MCQA) is a challenging task in machine reading comprehension. The main challenge in MCQA is to extract "evidence" from the given context that su…
Interpretable Rumor Detection in Microblogs by Attending to User Interactions
Ling Min Serena Khoo, Hai Leong Chieu, Zhong Qian +1
We address rumor detection by learning to differentiate between the community's response to real and fake claims in microblogs. Existing state-of-the-art models are based on tree m…
Multi-level Head-wise Match and Aggregation in Transformer for Textual Sequence Matching
Shuohang Wang, Yunshi Lan, Yi Tay +2
Transformer has been successfully applied to many natural language processing tasks. However, for textual sequence matching, simple matching between the representation of a pair of…
Multimodal Story Generation on Plural Images
Jing Jiang
Traditionally, text generation models take in a sequence of text as input, and iteratively generate the next most probable word using pre-trained parameters. In this work, we propo…