43 citations · 211 across the 38 of their papers we have counts for
22 papers · 1 filter
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…
Brain-like Functional Organization within Large Language Models
Haiyang Sun, Lin Zhao, Zihao Wu +7
The human brain has long inspired the pursuit of artificial intelligence (AI). Recently, neuroimaging studies provide compelling evidence of alignment between the computational rep…
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…
A Systematic Assessment of OpenAI o1-Preview for Higher Order Thinking in Education
Ehsan Latif, Yifan Zhou, Shuchen Guo +24
As artificial intelligence (AI) continues to advance, it demonstrates capabilities comparable to human intelligence, with significant potential to transform education and workforce…
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…
Evaluation of OpenAI o1: Opportunities and Challenges of AGI
Tianyang Zhong, Zhengliang Liu, Yi Pan +74
This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, includi…
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…
MGH Radiology Llama: A Llama 3 70B Model for Radiology
Yucheng Shi, Peng Shu, Zhengliang Liu +5
In recent years, the field of radiology has increasingly harnessed the power of artificial intelligence (AI) to enhance diagnostic accuracy, streamline workflows, and improve patie…
Brain Dialogue Interface (BDI): A User-Friendly fMRI Model for Interactive Brain Decoding
Heng Huang, Lin Zhao, Zihao Wu +5
Brain decoding techniques are essential for understanding the neurocognitive system. Although numerous methods have been introduced in this field, accurately aligning complex exter…
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…
Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysis
Shaochen Xu, Zihao Wu, Huaqin Zhao +7
In this study, we leverage LLM to enhance the semantic analysis and develop similarity metrics for texts, addressing the limitations of traditional unsupervised NLP metrics like RO…
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…
Understanding LLMs: A Comprehensive Overview from Training to Inference
Yiheng Liu, Hao He, Tianle Han +18
The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There's an increasing focus on cos…
Revolutionizing Finance with LLMs: An Overview of Applications and Insights
Huaqin Zhao, Zhengliang Liu, Zihao Wu +16
In recent years, Large Language Models (LLMs) like ChatGPT have seen considerable advancements and have been applied in diverse fields. Built on the Transformer architecture, these…