4 papers · 1 filter
Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models
Wanlong Liu, Yichen Xiao, Dingyi Zeng +3
Post-Training Quantization (PTQ) is pivotal for deploying large language models (LLMs) within resource-limited settings by significantly reducing resource demands. However, existin…
A Compressive Memory-based Retrieval Approach for Event Argument Extraction
Wanlong Liu, Enqi Zhang, Li Zhou +5
Recent works have demonstrated the effectiveness of retrieval augmentation in the Event Argument Extraction (EAE) task. However, existing retrieval-based EAE methods have two main…
Beyond Single-Event Extraction: Towards Efficient Document-Level Multi-Event Argument Extraction
Wanlong Liu, Li Zhou, Dingyi Zeng +6
Recent mainstream event argument extraction methods process each event in isolation, resulting in inefficient inference and ignoring the correlations among multiple events. To addr…
Utilizing Contextual Clues and Role Correlations for Enhancing Document-level Event Argument Extraction
Wanlong Liu, Dingyi Zeng, Li Zhou +6
Document-level event argument extraction is a crucial yet challenging task within the field of information extraction. Current mainstream approaches primarily focus on the informat…