3 citations · 9 across the 8 of their papers we have counts for
5 papers · 1 filter
Extracting Events Like Code: A Multi-Agent Programming Framework for Zero-Shot Event Extraction
Quanjiang Guo, Sijie Wang, Jinchuan Zhang +4
Zero-shot event extraction (ZSEE) remains a significant challenge for large language models (LLMs) due to the need for complex reasoning and domain-specific understanding. Direct p…
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training
Quanjiang Guo, Jinchuan Zhang, Sijie Wang +4
Few-Shot Relation Extraction (FSRE) remains a challenging task due to the scarcity of annotated data and the limited generalization capabilities of existing models. Although large…
BANER: Boundary-Aware LLMs for Few-Shot Named Entity Recognition
Quanjiang Guo, Yihong Dong, Ling Tian +3
Despite the recent success of two-stage prototypical networks in few-shot named entity recognition (NER), challenges such as over/under-detected false spans in the span detection s…
Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering
Yu Zhang, Kehai Chen, Xuefeng Bai +3
Knowledge graph question answering (KGQA) involves answering natural language questions by leveraging structured information stored in a knowledge graph. Typically, KGQA initially…
TieFake: Title-Text Similarity and Emotion-Aware Fake News Detection
Quanjiang Guo, Zhao Kang, Ling Tian +1
Fake news detection aims to detect fake news widely spreading on social media platforms, which can negatively influence the public and the government. Many approaches have been dev…