1 citations · 1 across the 12 of their papers we have counts for
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CTR-Guided Generative Query Suggestion in Conversational Search
Erxue Min, Hsiu-Yuan Huang, Xihong Yang +7
Generating effective query suggestions in conversational search requires aligning model outputs with user preferences, which is challenging due to sparse and noisy click signals. W…
From Prompting to Alignment: A Generative Framework for Query Recommendation
Erxue Min, Hsiu-Yuan Huang, Xihong Yang +7
In modern search systems, search engines often suggest relevant queries to users through various panels or components, helping refine their information needs. Traditionally, these…
Hgformer: Hyperbolic Graph Transformer for Recommendation
Xin Yang, Xingrun Li, Heng Chang +8
The cold start problem is a challenging problem faced by most modern recommender systems. By leveraging knowledge from other domains, cross-domain recommendation can be an effectiv…
DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System
Xihong Yang, Heming Jing, Zixing Zhang +10
Benefiting from the strong reasoning capabilities, Large language models (LLMs) have demonstrated remarkable performance in recommender systems. Various efforts have been made to d…
Hyperbolic Knowledge Transfer in Cross-Domain Recommendation System
Xin Yang, Heng Chang, Zhijian Lai +6
Cross-Domain Recommendation (CDR) seeks to utilize knowledge from different domains to alleviate the problem of data sparsity in the target recommendation domain, and it has been g…
Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer
Erxue Min, Yu Rong, Tingyang Xu +6
Click-Through Rate (CTR) prediction, which aims to estimate the probability that a user will click an item, is an essential component of online advertising. Existing methods mainly…