Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

With the widespread application of the Transformer architecture in various modalities,
including vision, the technology of large language models is evolving from a single modality …

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 …

We present QLoRA, an efficient finetuning approach that reduces memory usage enough to
finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit …

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

Abstract Language models are increasingly being deployed for general problem solving
across a wide range of tasks, but are still confined to token-level, left-to-right decision …

Large language models (LLMs) demonstrate powerful capabilities, but they still face
challenges in practical applications, such as hallucinations, slow knowledge updates, and …

Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

Like humans, large language models (LLMs) do not always generate the best output on their
first try. Motivated by how humans refine their written text, we introduce Self-Refine, an …