6 papers
AlpaCare:Instruction-tuned Large Language Models for Medical Application
Xinlu Zhang, Chenxin Tian, Xianjun Yang +3
Instruction-finetuning (IFT) has become crucial in aligning Large Language Models (LLMs) with diverse human needs and has shown great potential in medical applications. However, pr…
MMFakeBench: A Mixed-Source Multimodal Misinformation Detection Benchmark for LVLMs
Xuannan Liu, Zekun Li, Peipei Li +6
Current multimodal misinformation detection (MMD) methods often assume a single source and type of forgery for each sample, which is insufficient for real-world scenarios where mul…
GraphFM: Graph Factorization Machines for Feature Interaction Modeling
Shu Wu, Zekun Li, Yunyue Su +3
Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand…
MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific Understanding
Zekun Li, Xianjun Yang, Kyuri Choi +11
Scientific figure interpretation is a crucial capability for AI-driven scientific assistants built on advanced Large Vision Language Models. However, current datasets and benchmark…
FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMs
Xuannan Liu, Peipei Li, Huaibo Huang +6
The massive generation of multimodal fake news involving both text and images exhibits substantial distribution discrepancies, prompting the need for generalized detectors. However…
Large Language Models as Zero-shot Dialogue State Tracker through Function Calling
Zekun Li, Zhiyu Zoey Chen, Mike Ross +7
Large language models (LLMs) are increasingly prevalent in conversational systems due to their advanced understanding and generative capabilities in general contexts. However, thei…