4 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…