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Large language model-based paper classification framework with key-insight extraction and confidence-weighted voting

Zihan Song Shan Huang Ngeemasara Thapa Xin Zhang Byung-Kwon Park Jie Lu Wenyang Li Wenbin Liu Bei Zhan Jianfei Li
· 0 citations · 46 references

TL;DR

An LLM-based framework is proposed that leverages full-text key-insight extraction to enhance literature classification and implemented a confidence-weighted voting (CWV) mechanism using multiple LLMs to improve robustness.

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