483 citations · 4.2k across the 70 of their papers we have counts for
8 papers · 1 filter
MR.Rec: Synergizing Memory and Reasoning for Personalized Recommendation Assistant with LLMs
Jiani Huang, Xingchen Zou, Lianghao Xia +1
The application of Large Language Models (LLMs) in recommender systems faces key challenges in delivering deep personalization and intelligent reasoning, especially for interactive…
Adversarial Demonstration Learning for Low-resource NER Using Dual Similarity
Guowen Yuan, Tien-Hsuan Wu, Lianghao Xia +1
We study the problem of named entity recognition (NER) based on demonstration learning in low-resource scenarios. We identify two issues in demonstration construction and model tra…
RecGPT: A Foundation Model for Sequential Recommendation
Yangqin Jiang, Xubin Ren, Lianghao Xia +3
This work addresses a fundamental barrier in recommender systems: the inability to generalize across domains without extensive retraining. Traditional ID-based approaches fail enti…
Pre-training for Recommendation Unlearning
Guoxuan Chen, Lianghao Xia, Chao Huang
Modern recommender systems powered by Graph Neural Networks (GNNs) excel at modeling complex user-item interactions, yet increasingly face scenarios requiring selective forgetting…
AI-Researcher: Autonomous Scientific Innovation
Jiabin Tang, Lianghao Xia, Zhonghang Li +1
The powerful reasoning capabilities of Large Language Models (LLMs) in mathematics and coding, combined with their ability to automate complex tasks through agentic frameworks, pre…
Urban Computing in the Era of Large Language Models
Zhonghang Li, Lianghao Xia, Xubin Ren +4
Urban computing has emerged as a multidisciplinary field that harnesses data-driven technologies to address challenges and improve urban living. Traditional approaches, while benef…
LightGNN: Simple Graph Neural Network for Recommendation
Guoxuan Chen, Lianghao Xia, Chao Huang
Graph neural networks (GNNs) have demonstrated superior performance in collaborative recommendation through their ability to conduct high-order representation smoothing, effectivel…
DiffGraph: Heterogeneous Graph Diffusion Model
Zongwei Li, Lianghao Xia, Hua Hua +3
Recent advances in Graph Neural Networks (GNNs) have revolutionized graph-structured data modeling, yet traditional GNNs struggle with complex heterogeneous structures prevalent in…