What are parameters in the context of LLMs?

Parameters in LLMs are the internal variables or weights that the model learns and adjusts during its training process. These parameters essentially define the model's knowledge and capabilities, allowing it to make predictions or generate text based on the input it receives. The goal of training is to optimize these parameters to minimize errors. The other options are incorrect: Citations in generated answers are outputs, not internal settings. The websites an LLM can access relate to its data sources or retrieval augmented generation (RAG) capabilities, not its core internal parameters. The questions users ask are inputs to the LLM, not its internal parameters.