6 citations · 7 across the 5 of their papers we have counts for
5 papers
Mitigate Position Bias with Coupled Ranking Bias on CTR Prediction
Yao Zhao, Zhining Liu, Tianchi Cai +3
Position bias, i.e., users' preference of an item is affected by its placing position, is well studied in the recommender system literature. However, most existing methods ignore t…
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts
Zhitian Xie, Yinger Zhang, Chenyi Zhuang +4
The application of mixture-of-experts (MoE) is gaining popularity due to its ability to improve model's performance. In an MoE structure, the gate layer plays a significant role in…
GreenFlow: A Computation Allocation Framework for Building Environmentally Sound Recommendation System
Xingyu Lu, Zhining Liu, Yanchu Guan +6
Given the enormous number of users and items, industrial cascade recommendation systems (RS) are continuously expanded in size and complexity to deliver relevant items, such as new…
Fast Chain-of-Thought: A Glance of Future from Parallel Decoding Leads to Answers Faster
Hongxuan Zhang, Zhining Liu, Yao Zhao +4
In this work, we propose FastCoT, a model-agnostic framework based on parallel decoding without any further training of an auxiliary model or modification to the LLM itself. FastCo…
Adversarial Learning for Incentive Optimization in Mobile Payment Marketing
Xuanying Chen, Zhining Liu, Li Yu +5
Many payment platforms hold large-scale marketing campaigns, which allocate incentives to encourage users to pay through their applications. To maximize the return on investment, i…