Causal Agent based on Large Language Model

Understand

The large language model (LLM) has achieved significant success across various domains.

• However, the inherent complexity of causal problems and causal theory poses challenges in accurately describing them in natural language, making it difficult for LLM to comprehend and use them effectively.
• Causal methods are not easily conveyed through natural language, which hinders LLM's ability to apply them accurately.
• Additionally, causal datasets are typically tabular, while LLM excels in handling natural language data, creating a structural mismatch that impedes effective reasoning with tabular data.