24 citations · 87 across the 13 of their papers we have counts for
13 papers
PUMGPT: A Large Vision-Language Model for Product Understanding
Wei Xue, Zongyi Guo, Baoliang Cui +5
E-commerce platforms benefit from accurate product understanding to enhance user experience and operational efficiency. Traditional methods often focus on isolated tasks such as at…
Improving Text Matching in E-Commerce Search with A Rationalizable, Intervenable and Fast Entity-Based Relevance Model
Jiong Cai, Yong Jiang, Yue Zhang +10
Discovering the intended items of user queries from a massive repository of items is one of the main goals of an e-commerce search system. Relevance prediction is essential to the…
Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees
Yibo Wang, Wenhao Yang, Wei Jiang +5
Projection-free online learning has drawn increasing interest due to its efficiency in solving high-dimensional problems with complicated constraints. However, most existing projec…
CN 2-1 and CS 5-4 observations toward Arp 299 with the SMA
Junzhi Wang, Chunhua Qi, Shanghuo Li +1
Dense gas is the key for understanding star formation in galaxies. We present high resolution () observations of CN 2-1 and CS 5-4 as dense gas tracers toward Arp 299, a m…
Shape Controllable Virtual Try-on for Underwear Models
Xin Gao, Zhenjiang Liu, Zunlei Feng +4
Image virtual try-on task has abundant applications and has become a hot research topic recently. Existing 2D image-based virtual try-on methods aim to transfer a target clothing i…
SGPT: Semantic Graphs based Pre-training for Aspect-based Sentiment Analysis
Yong Qian, Zhongqing Wang, Rong Xiao +2
Previous studies show effective of pre-trained language models for sentiment analysis. However, most of these studies ignore the importance of sentimental information for pre-train…
Path-based Deep Network for Candidate Item Matching in Recommenders
Houyi Li, Zhihong Chen, Chenliang Li +5
The large-scale recommender system mainly consists of two stages: matching and ranking. The matching stage (also known as the retrieval step) identifies a small fraction of relevan…
Understanding Chinese Video and Language via Contrastive Multimodal Pre-Training
Chenyi Lei, Shixian Luo, Yong Liu +6
The pre-trained neural models have recently achieved impressive performances in understanding multimodal content. However, it is still very challenging to pre-train neural models f…
A Hybrid Bandit Framework for Diversified Recommendation
Qinxu Ding, Yong Liu, Chunyan Miao +2
The interactive recommender systems involve users in the recommendation procedure by receiving timely user feedback to update the recommendation policy. Therefore, they are widely…
Pre-training Graph Transformer with Multimodal Side Information for Recommendation
Yong Liu, Susen Yang, Chenyi Lei +5
Side information of items, e.g., images and text description, has shown to be effective in contributing to accurate recommendations. Inspired by the recent success of pre-training…
Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers
Ya Zhao, Rui Xu, Xinchao Wang +3
Lip reading has witnessed unparalleled development in recent years thanks to deep learning and the availability of large-scale datasets. Despite the encouraging results achieved, t…
Recent Advances in Diversified Recommendation
Qiong Wu, Yong Liu, Chunyan Miao +3
With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not. In recen…
Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning
Ryuichi Takanobu, Tao Zhuang, Minlie Huang +3
In this paper, we investigate the task of aggregating search results from heterogeneous sources in an E-commerce environment. First, unlike traditional aggregated web search that m…