43 citations · 167 across the 31 of their papers we have counts for
32 papers
SAMed-2: Selective Memory Enhanced Medical Segment Anything Model
Zhiling Yan, Sifan Song, Dingjie Song +11
Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…
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…
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…
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…
Large Language Models for Manufacturing
Yiwei Li, Huaqin Zhao, Hanqi Jiang +21
The rapid advances in Large Language Models (LLMs) have the potential to transform manufacturing industry, offering new opportunities to optimize processes, improve efficiency, and…
ECHOPulse: ECG controlled echocardio-grams video generation
Yiwei Li, Sekeun Kim, Zihao Wu +8
Echocardiography (ECHO) is essential for cardiac assessments, but its video quality and interpretation heavily relies on manual expertise, leading to inconsistent results from clin…
EchoFM: Foundation Model for Generalizable Echocardiogram Analysis
Sekeun Kim, Pengfei Jin, Sifan Song +6
Foundation models have recently gained significant attention because of their generalizability and adaptability across multiple tasks and data distributions. Although medical found…
Analyzing Nobel Prize Literature with Large Language Models
Zhenyuan Yang, Zhengliang Liu, Jing Zhang +19
This study examines the capabilities of advanced Large Language Models (LLMs), particularly the o1 model, in the context of literary analysis. The outputs of these models are compa…
LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting
Md Kowsher, Md. Shohanur Islam Sobuj, Nusrat Jahan Prottasha +3
Time series forecasting remains a challenging task, particularly in the context of complex multiscale temporal patterns. This study presents LLM-Mixer, a framework that improves fo…
HARP: Human-Assisted Regrouping with Permutation Invariant Critic for Multi-Agent Reinforcement Learning
Huawen Hu, Enze Shi, Chenxi Yue +7
Human-in-the-loop reinforcement learning integrates human expertise to accelerate agent learning and provide critical guidance and feedback in complex fields. However, many existin…
LLM-POTUS Score: A Framework of Analyzing Presidential Debates with Large Language Models
Zhengliang Liu, Yiwei Li, Oleksandra Zolotarevych +2
Large language models have demonstrated remarkable capabilities in natural language processing, yet their application to political discourse analysis remains underexplored. This pa…
GP-GPT: Large Language Model for Gene-Phenotype Mapping
Yanjun Lyu, Zihao Wu, Lu Zhang +11
Pre-trained large language models(LLMs) have attracted increasing attention in biomedical domains due to their success in natural language processing. However, the complex traits a…
Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagery
Zhenyuan Yang, Xuhui Lin, Qinyi He +10
The emergence of Large Language Models (LLMs) and multimodal foundation models (FMs) has generated heightened interest in their applications that integrate vision and language. Thi…
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
Zhiling Yan, Weixiang Sun, Rong Zhou +8
Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…
ALDM-Grasping: Diffusion-aided Zero-Shot Sim-to-Real Transfer for Robot Grasping
Yiwei Li, Zihao Wu, Huaqin Zhao +6
To tackle the "reality gap" encountered in Sim-to-Real transfer, this study proposes a diffusion-based framework that minimizes inconsistencies in grasping actions between the simu…
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning
Chong Ma, Hanqi Jiang, Wenting Chen +10
In the medical multi-modal frameworks, the alignment of cross-modality features presents a significant challenge. However, existing works have learned features that are implicitly…
LLMs for Coding and Robotics Education
Peng Shu, Huaqin Zhao, Hanqi Jiang +9
Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced te…
Assessing Large Language Models in Mechanical Engineering Education: A Study on Mechanics-Focused Conceptual Understanding
Jie Tian, Jixin Hou, Zihao Wu +11
This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering w…
Large Language Models for Robotics: Opportunities, Challenges, and Perspectives
Jiaqi Wang, Zihao Wu, Yiwei Li +17
Large language models (LLMs) have undergone significant expansion and have been increasingly integrated across various domains. Notably, in the realm of robot task planning, LLMs h…