13 citations · 75 across the 17 of their papers we have counts for
6 papers · 1 filter
Improving Variational Autoencoders with Density Gap-based Regularization
Jianfei Zhang, Jun Bai, Chenghua Lin +2
Variational autoencoders (VAEs) are one of the powerful unsupervised learning frameworks in NLP for latent representation learning and latent-directed generation. The classic optim…
Mixture of Attention Heads: Selecting Attention Heads Per Token
Xiaofeng Zhang, Yikang Shen, Zeyu Huang +3
Mixture-of-Experts (MoE) networks have been proposed as an efficient way to scale up model capacity and implement conditional computing. However, the study of MoE components mostly…
Entity Aware Syntax Tree Based Data Augmentation for Natural Language Understanding
Jiaxing Xu, Jianbin Cui, Jiangneng Li +2
Understanding the intention of the users and recognizing the semantic entities from their sentences, aka natural language understanding (NLU), is the upstream task of many natural…
Causal Intervention for Fairness in Multi-behavior Recommendation
Xi Wang, Wenjie Wang, Fuli Feng +3
Recommender systems usually learn user interests from various user behaviors, including clicks and post-click behaviors (e.g., like and favorite). However, these behaviors inevitab…
Query-Response Interactions by Multi-tasks in Semantic Search for Chatbot Candidate Retrieval
Libin Shi, Kai Zhang, Wenge Rong
Semantic search for candidate retrieval is an important yet neglected problem in retrieval-based Chatbots, which aims to select a bunch of candidate responses efficiently from a la…
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval
Yanmeng Wang, Jun Bai, Ye Wang +5
Dual-Encoders is a promising mechanism for answer retrieval in question answering (QA) systems. Currently most conventional Dual-Encoders learn the semantic representations of ques…