1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2024★ 1 cited
Recall, Retrieve and Reason: Towards Better In-Context Relation Extraction
Guozheng Li, Peng Wang, Wenjun Ke +5
Relation extraction (RE) aims to identify relations between entities mentioned in texts. Although large language models (LLMs) have demonstrated impressive in-context learning (ICL…
cs.CL2024★ 1 cited
Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors
Guozheng Li, Peng Wang, Jiajun Liu +4
Relation extraction (RE) is an important task that aims to identify the relationships between entities in texts. While large language models (LLMs) have revealed remarkable in-cont…
cs.CL2024
Empirical Analysis of Dialogue Relation Extraction with Large Language Models
Guozheng Li, Zijie Xu, Ziyu Shang +3
Dialogue relation extraction (DRE) aims to extract relations between two arguments within a dialogue, which is more challenging than standard RE due to the higher person pronoun fr…