34 citations · 130 across the 35 of their papers we have counts for
4 papers · 1 filter
Towards Alleviating the Object Bias in Prompt Tuning-based Factual Knowledge Extraction
Yuhang Wang, Dongyuan Lu, Chao Kong +1
Many works employed prompt tuning methods to automatically optimize prompt queries and extract the factual knowledge stored in Pretrained Language Models. In this paper, we observe…
Learning to Learn a Cold-start Sequential Recommender
Xiaowen Huang, Jitao Sang, Jian Yu +1
The cold-start recommendation is an urgent problem in contemporary online applications. It aims to provide users whose behaviors are literally sparse with as accurate recommendatio…
Knowledge Graph-enhanced Sampling for Conversational Recommender System
Mengyuan Zhao, Xiaowen Huang, Lixi Zhu +2
The traditional recommendation systems mainly use offline user data to train offline models, and then recommend items for online users, thus suffering from the unreliable estimatio…
Hashtag-centric Immersive Search on Social Media
Yuqi Gao, Jitao Sang, Tongwei Ren +1
Social media information distributes in different Online Social Networks (OSNs). This paper addresses the problem integrating the cross-OSN information to facilitate an immersive s…