2 citations · 2 across the 4 of their papers we have counts for
7 papers
Quantum-Classical Hybrid Molecular Autoencoder for Advancing Classical Decoding
Afrar Jahin, Yi Pan, Yingfeng Wang +2
Although recent advances in quantum machine learning (QML) offer significant potential for enhancing generative models, particularly in molecular design, a large array of classical…
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…
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…
Permutation Randomization on Nonsmooth Nonconvex Optimization: A Theoretical and Experimental Study
Wei Zhang, Arif Hassan Zidan, Afrar Jahin +2
While gradient-based optimizers that incorporate randomization often showcase superior performance on complex optimization, the theoretical foundations underlying this superiority…
HOME-3: High-Order Momentum Estimator with Third-Power Gradient for Convex and Smooth Nonconvex Optimization
Wei Zhang, Arif Hassan Zidan, Afrar Jahin +2
Momentum-based gradients are essential for optimizing advanced machine learning models, as they not only accelerate convergence but also advance optimizers to escape stationary poi…
Evaluating Mathematical Reasoning Across Large Language Models: A Fine-Grained Approach
Afrar Jahin, Arif Hassan Zidan, Wei Zhang +2
With the rapid advancement of Artificial Intelligence (AI), Large Language Models (LLMs) have significantly impacted a wide array of domains, including healthcare, engineering, sci…