34 citations · 36 across the 4 of their papers we have counts for
6 papers
Similar Users-Augmented Interest Network
Xiaolong Chen, Haoyi Zhao, Xu Huang +1
Click-through rate (CTR) prediction is one of the core tasks in recommender systems. User behavior sequences, as one of the most effective features, can accurately reflect user pre…
NDCG-Consistent Softmax Approximation with Accelerated Convergence
Yuanhao Pu, Defu Lian, Xiaolong Chen +3
Ranking tasks constitute fundamental components of extreme similarity learning frameworks, where extremely large corpora of objects are modeled through relative similarity relation…
CELA: Cost-Efficient Language Model Alignment for CTR Prediction
Xingmei Wang, Weiwen Liu, Xiaolong Chen +8
Click-Through Rate (CTR) prediction holds a paramount position in recommender systems. The prevailing ID-based paradigm underperforms in cold-start scenarios due to the skewed dist…
WESE: Weak Exploration to Strong Exploitation for LLM Agents
Xu Huang, Weiwen Liu, Xiaolong Chen +5
Recently, large language models (LLMs) have demonstrated remarkable potential as an intelligent agent. However, existing researches mainly focus on enhancing the agent's reasoning…
Understanding the planning of LLM agents: A survey
Xu Huang, Weiwen Liu, Xiaolong Chen +6
As Large Language Models (LLMs) have shown significant intelligence, the progress to leverage LLMs as planning modules of autonomous agents has attracted more attention. This surve…
Deep Group Interest Modeling of Full Lifelong User Behaviors for CTR Prediction
Qi Liu, Xuyang Hou, Haoran Jin +6
Extracting users' interests from their lifelong behavior sequence is crucial for predicting Click-Through Rate (CTR). Most current methods employ a two-stage process for efficiency…