33 citations · 72 across the 12 of their papers we have counts for
17 papers
Efficient Document Retrieval by End-to-End Refining and Quantizing BERT Embedding with Contrastive Product Quantization
Zexuan Qiu, Qinliang Su, Jianxing Yu +1
Efficient document retrieval heavily relies on the technique of semantic hashing, which learns a binary code for every document and employs Hamming distance to evaluate document di…
Federated Non-negative Matrix Factorization for Short Texts Topic Modeling with Mutual Information
Shijing Si, Jianzong Wang, Ruiyi Zhang +2
Non-negative matrix factorization (NMF) based topic modeling is widely used in natural language processing (NLP) to uncover hidden topics of short text documents. Usually, training…
Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering
Zenan Xu, Wanjun Zhong, Qinliang Su +2
A key challenge in video question answering is how to realize the cross-modal semantic alignment between textual concepts and corresponding visual objects. Existing methods mostly…
Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs
Bowen Tian, Qinliang Su, Jian Yin
The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number of anomalies are assumed to be available at the training stage, but t…
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…
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval
Zijing Ou, Qinliang Su, Jianxing Yu +5
With the need of fast retrieval speed and small memory footprint, document hashing has been playing a crucial role in large-scale information retrieval. To generate high-quality ha…