69 citations · 220 across the 37 of their papers we have counts for
5 papers · 1 filter
Pre-training with Large Language Model-based Document Expansion for Dense Passage Retrieval
Guangyuan Ma, Xing Wu, Peng Wang +2
In this paper, we systematically study the potential of pre-training with Large Language Model(LLM)-based document expansion for dense passage retrieval. Concretely, we leverage th…
PUNR: Pre-training with User Behavior Modeling for News Recommendation
Guangyuan Ma, Hongtao Liu, Xing Wu +4
News recommendation aims to predict click behaviors based on user behaviors. How to effectively model the user representations is the key to recommending preferred news. Existing w…
Query-as-context Pre-training for Dense Passage Retrieval
Xing Wu, Guangyuan Ma, Wanhui Qian +2
Recently, methods have been developed to improve the performance of dense passage retrieval by using context-supervised pre-training. These methods simply consider two passages fro…
PEN4Rec: Preference Evolution Networks for Session-based Recommendation
Dou Hu, Lingwei Wei, Wei Zhou +3
Session-based recommendation aims to predict user the next action based on historical behaviors in an anonymous session. For better recommendations, it is vital to capture user pre…
AutoSUM: Automating Feature Extraction and Multi-user Preference Simulation for Entity Summarization
Dongjun Wei, Yaxin Liu, Fuqing Zhu +4
Withthegrowthofknowledgegraphs, entity descriptions are becoming extremely lengthy. Entity summarization task, aiming to generate diverse, comprehensive, and representative summari…