22 citations · 33 across the 11 of their papers we have counts for
12 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…
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…
Vibe Medicine: Redefining Biomedical Research Through Human-AI Co-Work
Zihao Wu, Steven Xu, Bowen Chen +8
With the emergence of large language models (LLMs) and AI agent frameworks, the human-AI co-work paradigm known as Vibe Coding is changing how people code, making it more accessibl…
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…
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
Haoran Lu, Luyang Fang, Ruidong Zhang +47
Due to the remarkable capabilities and growing impact of large language models (LLMs), they have been deeply integrated into many aspects of society. Thus, ensuring their alignment…
MolQAE: Quantum Autoencoder for Molecular Representation Learning
Yi Pan, Hanqi Jiang, Wei Ruan +5
We introduce Quantum Molecular Autoencoder (MolQAE), the first quantum autoencoder to leverage the complete molecular structures. MolQAE uniquely maps SMILES strings directly to qu…
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…
From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches
Wei Ruan, Tianze Yang, Yifan Zhou +2
Model merging has achieved significant success, with numerous innovative methods proposed to enhance capabilities by combining multiple models. However, challenges persist due to t…
Large Language Models for Bioinformatics
Wei Ruan, Yanjun Lyu, Jing Zhang +52
With the rapid advancements in large language model (LLM) technology and the emergence of bioinformatics-specific language models (BioLMs), there is a growing need for a comprehens…
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…