Papers by Hongwen Yang

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Challenge:	Existing methods for generating abstracts involve collecting domain data and training corresponding models to complete the task of text summarization.
Approach:	They propose a method to train language models based on domain datasets and a Dynamic Graph of Thought (DGoT) which inherits the advantages of existing GoT prompt approach while reducing model reasoning cost.
Outcome:	The proposed method saves the cost of model training and improves reliability due to the hallucination problem of LLMs.