17 citations · 23 across the 16 of their papers we have counts for
5 papers · 1 filter
MORE: A Multimodal Object-Entity Relation Extraction Dataset with a Benchmark Evaluation
Liang He, Hongke Wang, Yongchang Cao +3
Extracting relational facts from multimodal data is a crucial task in the field of multimedia and knowledge graphs that feeds into widespread real-world applications. The emphasis…
FOAL: Fine-grained Contrastive Learning for Cross-domain Aspect Sentiment Triplet Extraction
Ting Xu, Zhen Wu, Huiyun Yang +1
Aspect Sentiment Triplet Extraction (ASTE) has achieved promising results while relying on sufficient annotation data in a specific domain. However, it is infeasible to annotate da…
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment Analysis
Fei Zhao, Chunhui Li, Zhen Wu +3
Multimodal Aspect-based Sentiment Analysis (MABSA) is a fine-grained Sentiment Analysis task, which has attracted growing research interests recently. Existing work mainly utilizes…
DRIN: Dynamic Relation Interactive Network for Multimodal Entity Linking
Shangyu Xing, Fei Zhao, Zhen Wu +3
Multimodal Entity Linking (MEL) is a task that aims to link ambiguous mentions within multimodal contexts to referential entities in a multimodal knowledge base. Recent methods for…
Dynamic Demonstrations Controller for In-Context Learning
Fei Zhao, Taotian Pang, Zhen Wu +3
In-context learning (ICL) is a new paradigm for natural language processing (NLP), where a large language model (LLM) observes a small number of demonstrations and a test instance…