74 citations · 99 across the 11 of their papers we have counts for
11 papers
Dynamic Token Reduction during Generation for Vision Language Models
Xiaoyu Liang, Chaofeng Guan, Jiaying Lu +3
Vision-Language Models (VLMs) have achieved notable success in multimodal tasks but face practical limitations due to the quadratic complexity of decoder attention mechanisms and a…
Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models
Jiaying Lu, Jinmeng Rao, Kezhen Chen +5
Large Vision-Language Models (LVLMs) offer remarkable benefits for a variety of vision-language tasks. However, a challenge hindering their application in real-world scenarios, par…
A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promises
Hejie Cui, Jiaying Lu, Ran Xu +14
This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs), including their construction, utilization models, and applications…
Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey
Chen Ling, Xujiang Zhao, Jiaying Lu +21
Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of app…
HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting
Jiaying Lu, Jiaming Shen, Bo Xiong +3
Medical decision-making processes can be enhanced by comprehensive biomedical knowledge bases, which require fusing knowledge graphs constructed from different sources via a unifor…
MuG: A Multimodal Classification Benchmark on Game Data with Tabular, Textual, and Visual Fields
Jiaying Lu, Yongchen Qian, Shifan Zhao +2
Previous research has demonstrated the advantages of integrating data from multiple sources over traditional unimodal data, leading to the emergence of numerous novel multimodal ap…
Closed-book Question Generation via Contrastive Learning
Xiangjue Dong, Jiaying Lu, Jianling Wang +1
Question Generation (QG) is a fundamental NLP task for many downstream applications. Recent studies on open-book QG, where supportive answer-context pairs are provided to models, h…
How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation
Hejie Cui, Jiaying Lu, Yao Ge +1
Graph neural networks (GNNs), as a group of powerful tools for representation learning on irregular data, have manifested superiority in various downstream tasks. With unstructured…
Weakly Supervised Concept Map Generation through Task-Guided Graph Translation
Jiaying Lu, Xiangjue Dong, Carl Yang
Recent years have witnessed the rapid development of concept map generation techniques due to their advantages in providing well-structured summarization of knowledge from free tex…
Evaluation of Unsupervised Entity and Event Salience Estimation
Jiaying Lu, Jinho D. Choi
Salience Estimation aims to predict term importance in documents. Due to few existing human-annotated datasets and the subjective notion of salience, previous studies typically gen…
Good, Better, Best: Textual Distractors Generation for Multiple-Choice Visual Question Answering via Reinforcement Learning
Jiaying Lu, Xin Ye, Yi Ren +1
Multiple-choice VQA has drawn increasing attention from researchers and end-users recently. As the demand for automatically constructing large-scale multiple-choice VQA data grows,…