This paper provides a comprehensive survey of recent advances and challenges in enabling large language models (LLMs) and multimodal LLMs (MLLMs) to understand and process tabular data. It introduces a taxonomy of tabular input representations and categorizes various table understanding tasks, highlighting critical research gaps and future opportunities in the field.