Considering that retrieved documents may not always answer the user’s question, the burden is placed on the LLM to discern if a given document contains the information to answer the question.
Inspired by the Chain-Of-Thought Reasoning (CoT), the study proposes to break down the instruction into several steps.
- Initially, the model should summarise the provided document for a comprehensive understanding.
- Then, it assesses whether the document directly addresses the question.
If so, the model generates a final response, based on the summarised information.
Otherwise, if the document is deemed irrelevant, the model issues the response as irrelevant.
Additionally, the proposed CoT fine-tuning method should effectively mitigate hallucinations in LLMs, enabling the LLM to answer questions based on the provided knowledge documents.
Below the instruction for CoT fine-tuning is shown…
