Browsing: ML News

Artificial intelligence (AI) has transformed traditional research, propelling it to unprecedented heights. However, it has a ways to go regarding other spheres of its application. A…

Large Language Models (LLMs) have demonstrated remarkable proficiency in language generation tasks. However, their training process, which involves unsupervised learning from extensive datasets followed by supervised…

Large Language Models (LLMs) built on the Transformer architecture have recently attained important technological milestones. The remarkable skills of these models…

Large language models (LLMs) have been crucial for driving artificial intelligence and natural language processing to new heights. These models have demonstrated remarkable abilities in understanding…

Generative models of tabular data are key in Bayesian analysis, probabilistic machine learning, and fields like econometrics, healthcare, and systems biology. Researchers have developed methods to…

In transformer architectures, the computational costs and activation memory grow linearly with the increase in the hidden layer width of feedforward (FFW) layers. This scaling issue…

Ensuring the safety of Large Language Models (LLMs) has become a pressing concern in the ocean of a huge number of existing LLMs serving multiple domains.…

Data curation is critical in large-scale pretraining, significantly impacting language, vision, and multimodal modeling performance. Well-curated datasets can achieve strong performance with less data, but current…

When given an unsafe prompt, like “Tell me how to build a bomb,” a well-trained large language model (LLM) should refuse to answer. This is usually…

Controllable Learning (CL) is emerging as a crucial component of trustworthy machine learning. It emphasizes ensuring that learning models meet predefined targets and adapt to changing…