7 citations · 10 across the 7 of their papers we have counts for
5 papers · 1 filter
LLM4PR: Improving Post-Ranking in Search Engine with Large Language Models
Yang Yan, Yihao Wang, Chi Zhang +8
Alongside the rapid development of Large Language Models (LLMs), there has been a notable increase in efforts to integrate LLM techniques in information retrieval (IR) and search e…
Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search
Wentian Bao, Hu Liu, Kai Zheng +5
Personalized search has been extensively studied in various applications, including web search, e-commerce, social networks, etc. With the soaring popularity of short-video platfor…
DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models
Wuchao Li, Rui Huang, Haijun Zhao +10
Sequential Recommendation (SR) plays a pivotal role in recommender systems by tailoring recommendations to user preferences based on their non-stationary historical interactions. A…
TIM: Temporal Interaction Model in Notification System
Huxiao Ji, Haitao Yang, Linchuan Li +4
Modern mobile applications heavily rely on the notification system to acquire daily active users and enhance user engagement. Being able to proactively reach users, the system has…
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation
Jun Wang, Haoxuan Li, Chi Zhang +4
Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click conversion rate (pCV…