activity
20232025
most citedEnhancing the Spatial Awareness Capability of Multi-Modal Large Language Model

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.MM2025

Towards Structure-aware Model for Multi-modal Knowledge Graph Completion

Linyu Li, Zhi Jin, Yichi Zhang +5

Knowledge graphs (KGs) play a key role in promoting various multimedia and AI applications. However, with the explosive growth of multi-modal information, traditional knowledge gra…

cs.CL2025

PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood Estimation

Zhengwei Tao, Pu Wu, Zhi Jin +8

Predicting future events based on news on the Web stands as one of the ultimate aspirations of artificial intelligence. Recent advances in large language model (LLM)-based systems…

cs.CL2025

Enhancing LLM Generation with Knowledge Hypergraph for Evidence-Based Medicine

Chengfeng Dou, Ying Zhang, Zhi Jin +4

Evidence-based medicine (EBM) plays a crucial role in the application of large language models (LLMs) in healthcare, as it provides reliable support for medical decision-making pro…

cs.CL2024

Exploring LLM-based Data Annotation Strategies for Medical Dialogue Preference Alignment

Chengfeng Dou, Ying Zhang, Zhi Jin +4

This research examines the use of Reinforcement Learning from AI Feedback (RLAIF) techniques to improve healthcare dialogue models, with the aim of tackling the challenges of prefe…

cs.CL2024

Integrating Physician Diagnostic Logic into Large Language Models: Preference Learning from Process Feedback

Chengfeng Dou, Zhi Jin, Wenpin Jiao +3

The use of large language models in medical dialogue generation has garnered significant attention, with a focus on improving response quality and fluency. While previous studies h…

cs.AI2023★ 2 cited

Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model

Yongqiang Zhao, Zhenyu Li, Zhi Jin +6

The Multi-Modal Large Language Model (MLLM) refers to an extension of the Large Language Model (LLM) equipped with the capability to receive and infer multi-modal data. Spatial awa…

cs.CL2023★ 2 cited

PlugMed: Improving Specificity in Patient-Centered Medical Dialogue Generation using In-Context Learning

Chengfeng Dou, Zhi Jin, Wenping Jiao +3

The patient-centered medical dialogue systems strive to offer diagnostic interpretation services to users who are less knowledgeable about medical knowledge, through emphasizing th…