25 citations · 38 across the 11 of their papers we have counts for
12 papers
MMKG-R1: Constructing Multimodal Knowledge Graphs via Reinforcement Learning
Zongyu Wu, Yilong Wang, Xiaochen Wang +5
Multimodal knowledge graphs (MMKGs) organize information across different modalities to support multimodal Graph Retrieval-Augmented Generation (RAG), which aims to improve the per…
KAMR: Grounding Generation via Knowledge-Aligned Multi-hop Retrieval
Xiaochen Wang, Yuan Zhong, Haoyu Wang +2
Graph-based retrieval-augmented generation increasingly relies on multi-hop retrieval, where answering a query requires composing multiple connected knowledge-graph triplets. Howev…
GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models
Yuan Zhong, Chuanwei Ruan, Moein Hasani +3
The rapid growth of online grocery shopping requires recommendation systems that capture cyclical purchasing behavior and diverse user intents. Traditional item-level methods face…
GPR: Empowering Generation with Graph-Pretrained Retriever
Xiaochen Wang, Zongyu Wu, Yuan Zhong +3
Graph retrieval-augmented generation (GRAG) places high demands on graph-specific retrievers. However, existing retrievers often rely on language models pretrained on plain text, l…
MEDMKG: Benchmarking Medical Knowledge Exploitation with Multimodal Knowledge Graph
Xiaochen Wang, Yuan Zhong, Lingwei Zhang +3
Medical deep learning models depend heavily on domain-specific knowledge to perform well on knowledge-intensive clinical tasks. Prior work has primarily leveraged unimodal knowledg…
Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models
Yuan Zhong, Xiaochen Wang, Jiaqi Wang +5
Synthesizing electronic health records (EHR) data has become a preferred strategy to address data scarcity, improve data quality, and model fairness in healthcare. However, existin…
FineRec:Exploring Fine-grained Sequential Recommendation
Xiaokun Zhang, Bo Xu, Youlin Wu +3
Sequential recommendation is dedicated to offering items of interest for users based on their history behaviors. The attribute-opinion pairs, expressed by users in their reviews fo…
PatentGPT: A Large Language Model for Intellectual Property
Zilong Bai, Ruiji Zhang, Linqing Chen +24
In recent years, large language models(LLMs) have attracted significant attention due to their exceptional performance across a multitude of natural language process tasks, and hav…
Recent Advances in Predictive Modeling with Electronic Health Records
Jiaqi Wang, Junyu Luo, Muchao Ye +8
The development of electronic health records (EHR) systems has enabled the collection of a vast amount of digitized patient data. However, utilizing EHR data for predictive modelin…
Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
Suhan Cui, Jiaqi Wang, Yuan Zhong +3
The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improv…
Hierarchical Pretraining on Multimodal Electronic Health Records
Xiaochen Wang, Junyu Luo, Jiaqi Wang +5
Pretraining has proven to be a powerful technique in natural language processing (NLP), exhibiting remarkable success in various NLP downstream tasks. However, in the medical domai…
MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation
Yuan Zhong, Suhan Cui, Jiaqi Wang +7
Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in…