133 citations · 139 across the 5 of their papers we have counts for
5 papers
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
ByteDance Seed, :, Jiaze Chen +267
We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…
Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems
Xiaohui Chen, Jiankai Sun, Taiqing Wang +3
Data subsampling is widely used to speed up the training of large-scale recommendation systems. Most subsampling methods are model-based and often require a pre-trained pilot model…
Label Inference Attack against Split Learning under Regression Setting
Shangyu Xie, Xin Yang, Yuanshun Yao +3
As a crucial building block in vertical Federated Learning (vFL), Split Learning (SL) has demonstrated its practice in the two-party model training collaboration, where one party h…
DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation
Liangwei Yang, Shengjie Wang, Yunzhe Tao +4
Graph Neural Network (GNN) based recommender systems have been attracting more and more attention in recent years due to their excellent performance in accuracy. Representing user-…
Person Re-Identification by Discriminative Selection in Video Ranking
Taiqing Wang, Shaogang Gong, Xiatian Zhu +1
Current person re-identification (ReID) methods typically rely on single-frame imagery features, whilst ignoring space-time information from image sequences often available in the…