3 citations · 3 across the 3 of their papers we have counts for
4 papers
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…
ITPP: Learning Disentangled Event Dynamics in Marked Temporal Point Processes
Wang-Tao Zhou, Zhao Kang, Ke Yan +1
Marked Temporal Point Processes (MTPPs) provide a principled framework for modeling asynchronous event sequences by conditioning on the history of past events. However, most existi…
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…