35 citations · 69 across the 5 of their papers we have counts for
6 papers
Cross-Domain Fake News Detection on Unseen Domains via LLM-Based Domain-Aware User Modeling
Xuankai Yang, Yan Wang, Jiajie Zhu +4
Cross-domain fake news detection (CD-FND) transfers knowledge from a source domain to a target domain and is crucial for real-world fake news mitigation. This task becomes particul…
Diagnostic-Guided Dynamic Profile Optimization for LLM-based User Simulators in Sequential Recommendation
Hongyang Liu, Zhu Sun, Tianjun Wei +3
Recent advances in large language models (LLMs) have enabled realistic user simulators for developing and evaluating recommender systems (RSs). However, existing LLM-based simulato…
Causal-Invariant Cross-Domain Out-of-Distribution Recommendation
Jiajie Zhu, Yan Wang, Feng Zhu +3
Cross-Domain Recommendation (CDR) aims to leverage knowledge from a relatively data-richer source domain to address the data sparsity problem in a relatively data-sparser target do…
Large Language Models for Intent-Driven Session Recommendations
Zhu Sun, Hongyang Liu, Xinghua Qu +3
Intent-aware session recommendation (ISR) is pivotal in discerning user intents within sessions for precise predictions. Traditional approaches, however, face limitations due to th…
Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions, and Prospects
Xinghua Qu, Hongyang Liu, Zhu Sun +4
Conversational recommender systems (CRSs) have become crucial emerging research topics in the field of RSs, thanks to their natural advantages of explicitly acquiring user preferen…
DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
Zhu Sun, Hui Fang, Jie Yang +5
Recently, one critical issue looms large in the field of recommender systems -- there are no effective benchmarks for rigorous evaluation -- which consequently leads to unreproduci…