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Section 1: The Quadratic Wall – Deconstructing the Scaling Limits of Self-Attention The remarkable success of Transformer architectures across a spectrum of artificial intelligence domains is rooted in the self-attention Read More …
Executive Summary This report examines a foundational paradigm shift in the development of large language models (LLMs): the native integration of external knowledge during the model’s foundational training process. While Read More …
The Scaling Barrier: Deconstructing the Transformer’s Quadratic Bottleneck The Transformer architecture, introduced in 2017, has become the cornerstone of modern machine learning, particularly in natural language processing.1 Its success is Read More …
The Paradigm of Progressive Model Growth The predominant paradigm in deep learning has long been centered on static architectures. In this conventional workflow, a neural network’s structure—its depth, width, and Read More …
1. Executive Summary: Navigating the Quantization Frontier The rapid growth in the scale of large language models (LLMs) and other deep neural networks has necessitated a parallel evolution in model Read More …
Executive Summary Cross-lingual transfer learning has emerged as a cornerstone of modern Natural Language Processing (NLP), offering a powerful paradigm to mitigate the profound linguistic inequality prevalent in the digital Read More …
Executive Summary The widespread adoption of large language models (LLMs) has brought a critical challenge to the forefront of inference engineering: managing the Key-Value (KV) cache. While the KV cache Read More …
Introduction: Beyond Classical Knowledge Distillation Knowledge Distillation (KD) has emerged as a cornerstone technique in machine learning, fundamentally addressing the tension between model performance and deployment efficiency.1 As deep neural Read More …
Introduction to Model Over-Parameterization and the Imperative for Efficiency The Challenge of Scaling Deep Learning Models The contemporary landscape of artificial intelligence is dominated by a paradigm of scale. The Read More …
The New Paradigm of Automated Discovery Scientific discovery is undergoing a profound transformation, evolving from an era where artificial intelligence served as a collection of specialized computational tools into a Read More …