activity
20232026
most citedTowards Better Chain-of-Thought Prompting Strategies: A Survey

25 citations · 54 across the 28 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.MM2023★ 17 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 25 cited

Towards Better Chain-of-Thought Prompting Strategies: A Survey

Zihan Yu, Liang He, Zhen Wu +2

Chain-of-Thought (CoT), a step-wise and coherent reasoning chain, shows its impressive strength when used as a prompting strategy for large language models (LLM). Recent years, the…