Uni-LoRA: Ultra-Efficient Parameter Reduction For LLM Training Low-Rank Adaptation (LoRA) revolutionized how we fine-tune large language models by introducing parameter-efficient training methods that constrain weight updates to low-rank matrix decompositions (Hu... computational efficiency isometric projections linear algebra LoRA machine learning mathematics neural networks optimization parameter efficiency projection methods
Scaling Laws Unveiled: The Mathematical Blueprint Behind Smarter, Cheaper AI Models Training a state-of-the-art language model can cost tens of millions of dollars and months of computation time, not to mention the expertise needed for development. Yet until now, researchers have bee... AI Chinchilla deep learning GPT-3 language models machine learning neural networks optimization principal component analysis scaling laws statistical methodology
Agentic Neural Networks: Self-Evolving Multi-Agent Systems Through Textual Backpropagation The landscape of artificial intelligence is rapidly evolving as researchers explore new ways to harness the collaborative power of multiple Large Language Models (LLMs). A groundbreaking paper from Lu... artificial intelligence LLMs multi-agent systems neural networks optimization textual backpropagation