Large language models (LLMs) are gaining increasing popularity in both academia and
industry, owing to their unprecedented performance in various applications. As LLMs …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Evaluating large language model (LLM) based chat assistants is challenging due to their
broad capabilities and the inadequacy of existing benchmarks in measuring human …

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

Large Language Models (LLMs) have unlocked new capabilities and applications; however,
evaluating the alignment with human preferences still poses significant challenges. To …

We introduce MMMU: a new benchmark designed to evaluate multimodal models on
massive multi-discipline tasks demanding college-level subject knowledge and deliberate …

We introduce Mixtral 8x7B, a Sparse Mixture of Experts (SMoE) language model. Mixtral has
the same architecture as Mistral 7B, with the difference that each layer is composed of 8 …

Abstract Multi-modal Large Language Models (MLLMs) have demonstrated impressive
instruction abilities across various open-ended tasks. However previous methods have …