The inherent capabilities of pretrained large language models are notable, yet achieving desired behaviors often requires additional adaptation. When dealing with models whose weights are kept private, the challenge intensifies, rendering tuning either excessively...

Large Language Models (LLMs) have exhibited remarkable prowess across various natural language processing tasks. However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language. Addressing...

Large Language Models (LLMs) have emerged as a transformative force in artificial intelligence, offering remarkable capabilities in processing and generating language-based responses. LLMs are being used in many applications, from automated customer service to...

Stable AI has recently released a new state-of-the-art model, Stable-Code-3B, designed for code completion in various programming languages with multiple additional capabilities. The model is a follow-up on the Stable Code Alpha 3B. It is trained on 1.3 trillion...

The Natural Language Generation (NLG) field stands at the intersection of linguistics and artificial intelligence. It focuses on the creation of human-like text by machines. Recent advancements in Large Language Models (LLMs) have revolutionized NLG, significantly...

Mixture-of-Experts (MoE) is an architecture based on the “divide and conquer” principle to solve complex tasks. Multiple individual machine learning (ML) models (called experts) work individually based on their specializations to provide the most optimal results. To...