22 citations · 85 across the 16 of their papers we have counts for
16 papers
Zero-Indexing Internet Search Augmented Generation for Large Language Models
Guangxin He, Zonghong Dai, Jiangcheng Zhu +6
Retrieval augmented generation has emerged as an effective method to enhance large language model performance. This approach typically relies on an internal retrieval module that u…
3D Scene Creation and Rendering via Rough Meshes: A Lighting Transfer Avenue
Bowen Cai, Yujie Li, Yuqin Liang +4
This paper studies how to flexibly integrate reconstructed 3D models into practical 3D modeling pipelines such as 3D scene creation and rendering. Due to the technical difficulty,…
DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization
Ben Xue, Shenghui Ran, Quan Chen +3
Image color harmonization algorithm aims to automatically match the color distribution of foreground and background images captured in different conditions. Previous deep learning…
Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation
Jian Zhang, Yuanqing Zhang, Huan Fu +6
Neural Radiance Fields (NeRF) have emerged as a potent paradigm for representing scenes and synthesizing photo-realistic images. A main limitation of conventional NeRFs is that the…
MAMDR: A Model Agnostic Learning Method for Multi-Domain Recommendation
Linhao Luo, Yumeng Li, Buyu Gao +7
Large-scale e-commercial platforms in the real-world usually contain various recommendation scenarios (domains) to meet demands of diverse customer groups. Multi-Domain Recommendat…
Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation
Bowen Cai, Huan Fu, Rongfei Jia +3
Adapting semantic segmentation models to new domains is an important but challenging problem. Recently enlightening progress has been made, but the performance of existing methods…
3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics
Huan Fu, Bowen Cai, Lin Gao +7
We introduce 3D-FRONT (3D Furnished Rooms with layOuts and semaNTics), a new, large-scale, and comprehensive repository of synthetic indoor scenes highlighted by professionally des…
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
Huan Fu, Shunming Li, Rongfei Jia +3
Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D shape of a given 2D image from a large 3D shape database. The common routine is to map 2D images and 3D shap…
3D-FUTURE: 3D Furniture shape with TextURE
Huan Fu, Rongfei Jia, Lin Gao +4
The 3D CAD shapes in current 3D benchmarks are mostly collected from online model repositories. Thus, they typically have insufficient geometric details and less informative textur…
TPG-DNN: A Method for User Intent Prediction Based on Total Probability Formula and GRU Loss with Multi-task Learning
Jingxing Jiang, Zhubin Wang, Fei Fang +1
The E-commerce platform has become the principal battleground where people search, browse and pay for whatever they want. Critical as is to improve the online shopping experience f…
Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records
Jiatu Shi, Huaxiu Yao, Xian Wu +4
E-commerce business is revolutionizing our shopping experiences by providing convenient and straightforward services. One of the most fundamental problems is how to balance the dem…
RNE: A Scalable Network Embedding for Billion-scale Recommendation
Jianbin Lin, Daixin Wang, Lu Guan +5
Nowadays designing a real recommendation system has been a critical problem for both academic and industry. However, due to the huge number of users and items, the diversity and dy…
POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion
Wen Chen, Pipei Huang, Jiaming Xu +7
Increasing demand for fashion recommendation raises a lot of challenges for online shopping platforms and fashion communities. In particular, there exist two requirements for fashi…
Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation
Yong Liu, Yinan Zhang, Qiong Wu +5
Interactive recommendation that models the explicit interactions between users and the recommender system has attracted a lot of research attentions in recent years. Most previous…
Deep Bayesian Multi-Target Learning for Recommender Systems
Qi Wang, Zhihui Ji, Huasheng Liu +1
With the increasing variety of services that e-commerce platforms provide, criteria for evaluating their success become also increasingly multi-targeting. This work introduces a mu…
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
Jizhe Wang, Pipei Huang, Huan Zhao +3
Recommender systems (RSs) have been the most important technology for increasing the business in Taobao, the largest online consumer-to-consumer (C2C) platform in China. The billio…