5 citations · 7 across the 8 of their papers we have counts for
4 papers · 1 filter
A Learnable Fully Interacted Two-Tower Model for Pre-Ranking System
Chao Xiong, Xianwen Yu, Wei Xu +3
Pre-ranking plays a crucial role in large-scale recommender systems by significantly improving the efficiency and scalability within the constraints of providing high-quality candi…
MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark
Shiqing Fan, Xichen Ding, Liang Zhang +1
LLMs' capabilities are enhanced by using function calls to integrate various data sources or API results into the context window. Typical tools include search, web crawlers, maps,…
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
Zixuan Li, Binzong Geng, Jing Xiong +11
Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeling user behavior sequences as te…
DOGR: Leveraging Document-Oriented Contrastive Learning in Generative Retrieval
Penghao Lu, Xin Dong, Yuansheng Zhou +3
Generative retrieval constitutes an innovative approach in information retrieval, leveraging generative language models (LM) to generate a ranked list of document identifiers (doci…