46 citations · 109 across the 13 of their papers we have counts for
13 papers
Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision
Sijie Cheng, Zhouhong Gu, Bang Liu +3
Taxonomies have been widely used in various domains to underpin numerous applications. Specially, product taxonomies serve an essential role in the e-commerce domain for the recomm…
Better Modeling the Programming World with Code Concept Graphs-augmented Multi-modal Learning
Martin Weyssow, Houari Sahraoui, Bang Liu
The progress made in code modeling has been tremendous in recent years thanks to the design of natural language processing learning approaches based on state-of-the-art model archi…
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation
Yuyan Chen, Yanghua Xiao, Bang Liu
Interpreting the predictions of existing Question Answering (QA) models is critical to many real-world intelligent applications, such as QA systems for healthcare, education, and f…
Refining BERT Embeddings for Document Hashing via Mutual Information Maximization
Zijing Ou, Qinliang Su, Jianxing Yu +3
Existing unsupervised document hashing methods are mostly established on generative models. Due to the difficulties of capturing long dependency structures, these methods rarely mo…
Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction
Zhexue Chen, Hong Huang, Bang Liu +2
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining…
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting
Tong Mo, Bang Liu
Keyword spotting aims to identify specific keyword audio utterances. In recent years, deep convolutional neural networks have been widely utilized in keyword spotting systems. Howe…