2 citations · 3 across the 9 of their papers we have counts for
9 papers
Why Thinking Hurts: Diagnosing and Rectifying Linguistic Inertia in Large Language Models for Recommendation
Luankang Zhang, Yonghao Huang, Hang Lv +6
Chain-of-Thought (CoT) reasoning is widely used to improve LLM performance, and recent foundation recommender models adopt it by generating textual reasoning before predicting targ…
MERIT: A Merchant Incentive Ranking Model for Hotel Search & Ranking
Shigang Quan, Hailong Tan, Shui Liu +5
Online Travel Platforms (OTPs) have been working on improving their hotel Search & Ranking (S&R) systems that facilitate efficient matching between consumers and hotels. Existing O…
DEEPER Insight into Your User: Directed Persona Refinement for Dynamic Persona Modeling
Aili Chen, Chengyu Du, Jiangjie Chen +6
To advance personalized applications such as recommendation systems and user behavior prediction, recent research increasingly adopts large language models (LLMs) for human -readab…
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying +9
Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful ou…
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…
Modeling User Viewing Flow Using Large Language Models for Article Recommendation
Zhenghao Liu, Zulong Chen, Moufeng Zhang +6
This paper proposes the User Viewing Flow Modeling (SINGLE) method for the article recommendation task, which models the user constant preference and instant interest from user-cli…
Optimal Propagation for Graph Neural Networks
Beidi Zhao, Boxin Du, Zhe Xu +2
Graph Neural Networks (GNNs) have achieved tremendous success in a variety of real-world applications by relying on the fixed graph data as input. However, the initial input graph…
Detecting Topology Attacks against Graph Neural Networks
Senrong Xu, Yuan Yao, Liangyue Li +3
Graph neural networks (GNNs) have been widely used in many real applications, and recent studies have revealed their vulnerabilities against topology attacks. To address this issue…