Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

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

Program synthesis has been long studied with recent approaches focused on directly using
the power of Large Language Models (LLMs) to generate code. Programming benchmarks …

Recently, remarkable progress has been made in automated task-solving through the use of
multiagents driven by large language models (LLMs). However, existing works primarily …

We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-
centric approach. While stronger language models can enhance multimodal capabilities, the …

Large language models (LLMs) have pushed the limits of natural language understanding
and exhibited excellent problem-solving ability. Despite the great success, most existing …

To parameter-efficiently fine-tune (PEFT) large language models (LLMs), the low-rank
adaptation (LoRA) method approximates the model changes $\Delta W\in\mathbb …

Large language models (LLMs), such as GPT-4, have shown remarkable performance in
natural language processing (NLP) tasks, including challenging mathematical reasoning …

In this paper, we unveil that Language Models (LMs) can acquire new capabilities by
assimilating parameters from homologous models without retraining or GPUs. We first …