Browsing: ML News
In the dynamic field of Artificial Intelligence (AI), the trajectory from one foundational model to another has represented an amazing paradigm shift. The escalating series of…
Large language models (LLMs) like GPT-4 require substantial computational power and memory, posing challenges for their efficient deployment. While sparsification methods have been developed to mitigate…
With the rise of Large Language Models (LLMs) in recent years, generative AI has made significant strides in the field of language processing, showcasing impressive abilities…
In the dynamic field of software development, integrating large language models (LLMs) has initiated a new chapter, especially in code intelligence. These sophisticated models have been…
Evaluating LLMs as versatile agents is crucial for their integration into practical applications. However, existing evaluation frameworks face challenges in benchmarking diverse scenarios, maintaining partially observable…
As Large Language Models (LLMs) gain prominence in high-stakes applications, understanding their decision-making processes becomes crucial to mitigate potential risks. The inherent opacity of these models…
Data scientists and ML engineers often need help to build full-stack applications. These professionals typically have a firm grasp of data and AI algorithms. Still, they…
One of the most exciting advancements in AI and machine learning has been speech generation using Large Language Models (LLMs). While effective in various applications, the…
With textual materials comprising a large portion of its content, the web is a continuously growing repository of real-world knowledge. Changes to information necessitate either the…
In language model alignment, the effectiveness of reinforcement learning from human feedback (RLHF) hinges on the excellence of the underlying reward model. A pivotal concern is…