765 citations · 1.9k across the 87 of their papers we have counts for
90 papers
ASTELD: A Six-Axis Classification Framework for Autonomous AI Agents - Design, Evaluation, and an OpenClaw Case Study
Siyuan Li, Peng Shu, Churan Yu +19
Autonomous AI agent platforms differ substantially in architecture, security, tool integration, execution, autonomy, and deployment, yet the field lacks a common classification sch…
Toward Vibe Medicine: A Self-Evolving Multi-Agent Framework for Clinical Decision Support
Qianxue Zhang, Yiming Ren, Shihuan Qin +18
In recent years, the advances of large language models and autonomous agents have revolutionized the healthcare field, facilitating diagnosis and improving treatment results. Howev…
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications
Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23
World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artificial general intelligence, ena…
Applications of Large Language Models in Radiation Oncology: From Workflow Automation to Clinical Intelligence
Yuzhen Ding, Jason Holmes, Yuexing Hao +12
Large language models (LLMs) have emerged as transformative tools in medicine, with strong capabilities in language understanding, reasoning, and structured information extraction.…
Empowering Locally Deployable Medical Agent via State Enhanced Logical Skills for FHIR-based Clinical Tasks
Wanrong Yang, Zhengliang Liu, Yuan Li +6
While Large Language Models demonstrate immense potential as proactive Medical Agents, their real-world deployment is severely bottlenecked by data scarcity under privacy constrain…
Thinking with Gaze: Sequential Eye-Tracking as Visual Reasoning Supervision for Medical VLMs
Yiwei Li, Yifan Zhou, Huaqin Zhao +6
Vision--language models (VLMs) process images as visual tokens, yet their intermediate reasoning is often carried out in text, which can be suboptimal for visually grounded radiolo…
Causal machine learning reveals age-dependent radiation dose effects on mandibular osteoradionecrosis
Jingyuan Chen, Yunze Yang, Olivia M. Muller +8
Distinguishing causal relationships from statistical correlations remains a fundamental challenge in clinical research, limiting the translation of observational findings into inte…
Large Language Models for Assisting American College Applications
Zhengliang Liu, Weihang You, Peng Shu +14
American college applications require students to navigate fragmented admissions policies, repetitive and conditional forms, and ambiguous questions that often demand cross-referen…
MoMoE: A Mixture of Expert Agent Model for Financial Sentiment Analysis
Peng Shu, Junhao Chen, Zhengliang Liu +8
We present a novel approach called Mixture of Mixture of Expert (MoMoE) that combines the strengths of Mixture-of-Experts (MoE) architectures with collaborative multi-agent framewo…
Causal Machine Learning Analysis of Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis in Head and Neck Cancer Radiotherapy
Jingyuan Chen, Zhong Liu, Yunze Yang +8
Mandible Osteoradionecrosis (ORN) is one of the most severe adverse events (AEs) for head and neck (H&N) cancer radiotherapy. Previous retrospective investigations on real-world da…
Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems
Sohan Shankar, Yi Pan, Hanqi Jiang +43
This position and survey paper identifies the emerging convergence of neuroscience, artificial general intelligence (AGI), and neuromorphic computing toward a unified research para…
Survey of HPC in US Research Institutions
Peng Shu, Junhao Chen, Zhengliang Liu +3
The rapid growth of AI, data-intensive science, and digital twin technologies has driven an unprecedented demand for high-performance computing (HPC) across the research ecosystem.…
Logic-of-Thought: Empowering Large Language Models with Logic Programs for Solving Puzzles in Natural Language
Naiqi Li, Peiyuan Liu, Zheng Liu +3
Solving puzzles in natural language poses a long-standing challenge in AI. While large language models (LLMs) have recently shown impressive capabilities in a variety of tasks, the…
AD-GPT: Large Language Models in Alzheimer's Disease
Ziyu Liu, Lintao Tang, Zeliang Sun +11
Large language models (LLMs) have emerged as powerful tools for medical information retrieval, yet their accuracy and depth remain limited in specialized domains such as Alzheimer'…
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions
Luyang Fang, Xiaowei Yu, Jiazhang Cai +23
The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational and data demands. This survey p…
Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology
Peilong Wang, Zhengliang Liu, Yiwei Li +12
Background: The radiation oncology clinical practice involves many steps relying on the dynamic interplay of abundant text data. Large language models have displayed remarkable cap…
QueEn: A Large Language Model for Quechua-English Translation
Junhao Chen, Peng Shu, Yiwei Li +7
Recent studies show that large language models (LLMs) are powerful tools for working with natural language, bringing advances in many areas of computational linguistics. However, t…
Foundation Models for Low-Resource Language Education (Vision Paper)
Zhaojun Ding, Zhengliang Liu, Hanqi Jiang +4
Recent studies show that large language models (LLMs) are powerful tools for working with natural language, bringing advances in many areas of computational linguistics. However, t…
A recent evaluation on the performance of LLMs on radiation oncology physics using questions of randomly shuffled options
Peilong Wang, Jason Holmes, Zhengliang Liu +4
Purpose: We present an updated study evaluating the performance of large language models (LLMs) in answering radiation oncology physics questions, focusing on the recently released…
Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research
Tianyang Zhong, Zhenyuan Yang, Zhengliang Liu +11
Low-resource languages serve as invaluable repositories of human history, embodying cultural evolution and intellectual diversity. Despite their significance, these languages face…
OracleSage: Towards Unified Visual-Linguistic Understanding of Oracle Bone Scripts through Cross-Modal Knowledge Fusion
Hanqi Jiang, Yi Pan, Junhao Chen +8
Oracle bone script (OBS), as China's earliest mature writing system, present significant challenges in automatic recognition due to their complex pictographic structures and diverg…
Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translation
Peng Shu, Junhao Chen, Zhengliang Liu +13
Large Language Models (LLMs) have demonstrated remarkable success across a wide range of tasks and domains. However, their performance in low-resource language translation, particu…
Towards Next-Generation Medical Agent: How o1 is Reshaping Decision-Making in Medical Scenarios
Shaochen Xu, Yifan Zhou, Zhengliang Liu +19
Artificial Intelligence (AI) has become essential in modern healthcare, with large language models (LLMs) offering promising advances in clinical decision-making. Traditional model…
EG-SpikeFormer: Eye-Gaze Guided Transformer on Spiking Neural Networks for Medical Image Analysis
Yi Pan, Hanqi Jiang, Junhao Chen +10
Neuromorphic computing has emerged as a promising energy-efficient alternative to traditional artificial intelligence, predominantly utilizing spiking neural networks (SNNs) implem…