Papers with recursive summarization

2 papers
DTCRS: Dynamic Tree Construction for Recursive Summarization (2025.acl-long)

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Challenge: Recursive summarization (RAG) is an important method for mitigating large model hallucinations and enhancing answer interpretability.
Approach: They propose a method that dynamically generates summary trees based on document structure and query semantics.
Outcome: The proposed method significantly reduces summary tree construction time and achieves substantial improvements across three QA tasks.
Prompted Opinion Summarization with GPT-3.5 (2023.findings-acl)

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Challenge: Recent years have seen several shifts in summarization research, including extractive models.
Approach: They propose a pipeline method for applying GPT-3.5 to summarize user reviews . they propose three new metrics targeting faithfulness, factuality, and genericity .
Outcome: The proposed methods perform well in opinion summarization, the authors show . they also show that standard evaluation metrics do not reflect this performance .

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