5 papers
SAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction
Quanjiang Guo, Chong Mu, Jiazhou Pan +4
Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for un…
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…
ViFP: A Framework for Visual False Positive Detection to Enhance Reasoning Reliability in VLMs
Ben Zhang, LuLu Yu, Lei Gao +3
During reasoning in vision-language models (VLMs), false positive (FP) reasoning occurs when a model produces the correct answer but follows an incorrect reasoning path, resulting…
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…