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20242026
most citedMasked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SGA-Flow-GRPO: Spatial Gradient-Guided Credit Assignment for Flow-GRPO

Yunkai Yang, Yudong Zhang, Xinying Chen +5

Reinforcement Learning (RL) has proven effective in aligning flow-based generative models with human preferences. Recently, Flow-GRPO has emerged as an efficient critic-free paradi…

cs.CV2026

ControlRef: Efficient Layout-Guided Multi-Instance Generation via Anchored 4D-RoPE

Yunkai Yang, Yudong Zhang, Xinying Chen +7

Layout-guided multi-instance generation is essential for controllable image synthesis in Multi-Modal Diffusion Transformers (MM-DiTs). However, integrating this capability into uni…

cs.IR2026

OneMall: One Architecture, More Scenarios -- End-to-End Generative Recommender Family at Kuaishou E-Commerce

Kun Zhang, Jingming Zhang, Wei Cheng +29

In the wave of generative recommendation, we present OneMall, an end-to-end generative recommendation framework tailored for e-commerce services at Kuaishou. Our OneMall systematic…

cs.CV2025

Task-Oriented Data Synthesis and Control-Rectify Sampling for Remote Sensing Semantic Segmentation

Yunkai Yang, Yudong Zhang, Kunquan Zhang +4

With the rapid progress of controllable generation, training data synthesis has become a promising way to expand labeled datasets and alleviate manual annotation in remote sensing…

cs.IR2024★ 1 cited

Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model

Wentao Ouyang, Xiuwu Zhang, Chaofeng Guo +8

In real-world advertising systems, conversions have different types in nature and ads can be shown in different display scenarios, both of which highly impact the actual conversion…