46 citations · 156 across the 24 of their papers we have counts for
7 papers · 1 filter
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study
Peilin Zhou, Meng Cao, You-Liang Huang +6
Large Multimodal Models (LMMs) have demonstrated impressive performance across various vision and language tasks, yet their potential applications in recommendation tasks with visu…
A Survey of Large Language Models in Medicine: Progress, Application, and Challenge
Hongjian Zhou, Fenglin Liu, Boyang Gu +16
Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a…
Qilin-Med-VL: Towards Chinese Large Vision-Language Model for General Healthcare
Junling Liu, Ziming Wang, Qichen Ye +3
Large Language Models (LLMs) have introduced a new era of proficiency in comprehending complex healthcare and biomedical topics. However, there is a noticeable lack of models in la…
Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
Qichen Ye, Junling Liu, Dading Chong +8
Integrating large language models (LLMs) into healthcare holds great potential but faces challenges. Pre-training LLMs from scratch for domains like medicine is resource-heavy and…
LLMRec: Benchmarking Large Language Models on Recommendation Task
Junling Liu, Chao Liu, Peilin Zhou +8
Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models. However,…
Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset
Junling Liu, Peilin Zhou, Yining Hua +8
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the l…
Is ChatGPT a Good Recommender? A Preliminary Study
Junling Liu, Chao Liu, Peilin Zhou +3
Recommendation systems have witnessed significant advancements and have been widely used over the past decades. However, most traditional recommendation methods are task-specific a…