6 citations · 9 across the 5 of their papers we have counts for
5 papers
REMOTE: A Unified Multimodal Relation Extraction Framework with Multilevel Optimal Transport and Mixture-of-Experts
Xinkui Lin, Yongxiu Xu, Minghao Tang +4
Multimodal relation extraction (MRE) is a crucial task in the fields of Knowledge Graph and Multimedia, playing a pivotal role in multimodal knowledge graph construction. However,…
MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillation
Longzheng Wang, Xiaohan Xu, Lei Zhang +5
Automatic detection of multimodal misinformation has gained a widespread attention recently. However, the potential of powerful Large Language Models (LLMs) for multimodal misinfor…
Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning
Yongquan He, Wenyuan Zhang, Xuancheng Huang +5
Instruction tuning for large language models (LLMs) can drive them to produce results consistent with human goals in specific downstream tasks. However, the process of continual in…
A Boundary Offset Prediction Network for Named Entity Recognition
Minghao Tang, Yongquan He, Yongxiu Xu +3
Named entity recognition (NER) is a fundamental task in natural language processing that aims to identify and classify named entities in text. However, span-based methods for NER t…
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning
Minghao Tang, Yongquan He, Yongxiu Xu +3
Fine-grained entity typing (FET) is an essential task in natural language processing that aims to assign semantic types to entities in text. However, FET poses a major challenge kn…