2 citations · 4 across the 9 of their papers we have counts for
9 papers
DivNet: Diversity-Aware Self-Correcting Sequential Recommendation Networks
Shuai Xiao, Zaifan Jiang
As the last stage of a typical \textit{recommendation system}, \textit{collective recommendation} aims to give the final touches to the recommended items and their layout so as to…
Pseudo Label Refinery for Unsupervised Domain Adaptation on Cross-dataset 3D Object Detection
Zhanwei Zhang, Minghao Chen, Shuai Xiao +7
Recent self-training techniques have shown notable improvements in unsupervised domain adaptation for 3D object detection (3D UDA). These techniques typically select pseudo labels,…
Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Models
Chen Ju, Haicheng Wang, Zeqian Li +4
Vision-Language Large Models (VLMs) have become primary backbone of AI, due to the impressive performance. However, their expensive computation costs, i.e., throughput and delay, i…
Enhancing Cross-domain Click-Through Rate Prediction via Explicit Feature Augmentation
Xu Chen, Zida Cheng, Jiangchao Yao +5
Cross-domain CTR (CDCTR) prediction is an important research topic that studies how to leverage meaningful data from a related domain to help CTR prediction in target domain. Most…
Forgedit: Text Guided Image Editing via Learning and Forgetting
Shiwen Zhang, Shuai Xiao, Weilin Huang
Text-guided image editing on real or synthetic images, given only the original image itself and the target text prompt as inputs, is a very general and challenging task. It require…
Automatic Deduction Path Learning via Reinforcement Learning with Environmental Correction
Shuai Xiao, Chen Pan, Min Wang +6
Automatic bill payment is an important part of business operations in fintech companies. The practice of deduction was mainly based on the total amount or heuristic search by divid…
Cross-domain Augmentation Networks for Click-Through Rate Prediction
Xu Chen, Zida Cheng, Shuai Xiao +2
Data sparsity is an important issue for click-through rate (CTR) prediction, particularly when user-item interactions is too sparse to learn a reliable model. Recently, many works…
Category-Oriented Representation Learning for Image to Multi-Modal Retrieval
Zida Cheng, Chen Ju, Shuai Xiao +5
The rise of multi-modal search requests from users has highlighted the importance of multi-modal retrieval (i.e. image-to-text or text-to-image retrieval), yet the more complex tas…
Tile Networks: Learning Optimal Geometric Layout for Whole-page Recommendation
Shuai Xiao, Zaifan Jiang, Shuang Yang
Finding optimal configurations in a geometric space is a key challenge in many technological disciplines. Current approaches either rely heavily on human domain expertise and are d…