1 citations · 1 across the 4 of their papers we have counts for
4 papers
Domain-Hierarchy Adaptation via Chain of Iterative Reasoning for Few-shot Hierarchical Text Classification
Ke Ji, Peng Wang, Wenjun Ke +4
Recently, various pre-trained language models (PLMs) have been proposed to prove their impressive performances on a wide range of few-shot tasks. However, limited by the unstructur…
Fast and Continual Knowledge Graph Embedding via Incremental LoRA
Jiajun Liu, Wenjun Ke, Peng Wang +7
Continual Knowledge Graph Embedding (CKGE) aims to efficiently learn new knowledge and simultaneously preserve old knowledge. Dominant approaches primarily focus on alleviating cat…
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…
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…