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Understanding what's happening behind large language models (LLMs) is essential in today's machine learning landscape.
Artificial intelligence (AI) research, particularly in the machine learning (ML) domain, continues to increase the amount of atten...
Semantic segmentation of the glottal area from high-speed videoendoscopic (HSV) sequences presents a critical challenge in larynge...
Breaking down videos into smaller, meaningful parts for vision models remains challenging, particularly for long videos. Vision mo...
Training large-scale AI models such as transformers and language models have become an indispensable yet highly demanding process ...
Reward functions play a crucial role in reinforcement learning (RL) systems, but their design presents significant challenges in b...
One of the most critical challenges in computational fluid dynamics (CFD) and machine learning (ML) is that high-resolution, 3D da...
Graphical User Interfaces (GUIs) are central to how users engage with software. However, building intelligent agents capable of ef...
Autoregressive (AR) models have changed the field of image generation, setting new benchmarks in producing high-quality visuals. T...
Ensuring the correctness of electronic designs is critical, as hardware flaws are permanent post-production and can compromise sof...
The pursuit of enhancing artificial intelligence (AI) capabilities is significantly influenced by human intelligence, particularly...
Mathematical reasoning has emerged as a critical frontier in artificial intelligence, particularly in developing Large Language Mo...
