The Challenge of Data Selection in LLM Pretraining Developing large language models entails substantial computational investment, especially when experimenting with…
Parameter-efficient fine-tuning (PEFT) methods, like low-rank adaptation (LoRA), allow large pre-trained foundation models to be adapted to downstream tasks using…
Vision-language models (VLMs) have become foundational components for multimodal AI systems, enabling autonomous agents to understand visual environments, reason over…