Browsing: ML News
In computational chemistry, molecules are often represented as molecular graphs, which must be converted into multidimensional vectors for processing, particularly in machine learning applications. This is…
Llama-3-Nephilim-v3-8B and llama-3-Nephilim-v3-8B-GGUF are two innovative models released on Hugging Face. Although these models were never explicitly trained for roleplay, they exhibit remarkable capability in this…
In the rapidly developing field of Artificial Intelligence, it is more important than ever to convert unstructured data into organized, useful information efficiently. Recently, a team…
Optimal transport is a mathematical discipline focused on determining the most efficient way to move mass between probability distributions. This field has wide-ranging applications in economics,…
Automating mathematical reasoning has long been a goal in artificial intelligence, with formal frameworks like Lean 4, Isabelle, and Coq playing a significant role. These frameworks…
As LLMs become increasingly integral to various AI tasks, their massive parameter sizes lead to high memory requirements and bandwidth consumption. While quantization-aware training (QAT) offers…
Evaluating conversational AI assistants, like GitHub Copilot Chat, is challenging due to their reliance on language models and chat-based interfaces. Existing metrics for conversational quality need…
Survey on Machine Learning-Powered Augmented Reality in Education: ML advances augmented reality (AR) across various educational fields, enhancing object visualizations and interaction capabilities. This survey outlines…
Evaluating the effectiveness of Large Language Model (LLM) compression techniques is a crucial challenge in AI. Compression methods like quantization aim to optimize LLM efficiency by…
Large Language Models (LLMs) have made significant strides in artificial intelligence, but their ability to process complex structured data, particularly graphs, remains challenging. In our interconnected…