3 citations · 7 across the 4 of their papers we have counts for
4 papers
Retrieval-style In-Context Learning for Few-shot Hierarchical Text Classification
Huiyao Chen, Yu Zhao, Zulong Chen +4
Hierarchical text classification (HTC) is an important task with broad applications, while few-shot HTC has gained increasing interest recently. While in-context learning (ICL) wit…
Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation
Tingjia Shen, Hao Wang, Jiaqing Zhang +5
Cross-Domain Sequential Recommendation (CDSR) aims to mine and transfer users' sequential preferences across different domains to alleviate the long-standing cold-start issue. Trad…
Side Information-Driven Session-based Recommendation: A Survey
Xiaokun Zhang, Bo Xu, Chenliang Li +3
The session-based recommendation (SBR) garners increasing attention due to its ability to predict anonymous user intents within limited interactions. Emerging efforts incorporate v…
Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation
Liangyue Li, Hanghang Tong, Nan Cao +3
In this paper, we study the problem of Team Member Replacement: given a team of people embedded in a social network working on the same task, find a good candidate who can fit in t…