activity
20192024
most citedMulti-Modal Knowledge Graph Construction and Application: A Survey

292 citations · 546 across the 54 of their papers we have counts for

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Showing 2023Show all

21 papers · 1 filter

cs.CL2023★ 2 cited

AspectMMKG: A Multi-modal Knowledge Graph with Aspect-aware Entities

Jingdan Zhang, Jiaan Wang, Xiaodan Wang +2

Multi-modal knowledge graphs (MMKGs) combine different modal data (e.g., text and image) for a comprehensive understanding of entities. Despite the recent progress of large-scale M…

cs.CV2023★ 3 cited

Towards Visual Taxonomy Expansion

Tinghui Zhu, Jingping Liu, Jiaqing Liang +5

Taxonomy expansion task is essential in organizing the ever-increasing volume of new concepts into existing taxonomies. Most existing methods focus exclusively on using textual sem…

cs.CL2023★ 3 cited

Can Large Language Models Understand Real-World Complex Instructions?

Qianyu He, Jie Zeng, Wenhao Huang +14

Large language models (LLMs) can understand human instructions, showing their potential for pragmatic applications beyond traditional NLP tasks. However, they still struggle with c…

cs.CL2023★ 13 cited

KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases

Xintao Wang, Qianwen Yang, Yongting Qiu +5

Large language models (LLMs) have demonstrated impressive impact in the field of natural language processing, but they still struggle with several issues regarding, such as complet…

cs.CL2023★ 2 cited

Translate Meanings, Not Just Words: IdiomKB's Role in Optimizing Idiomatic Translation with Language Models

Shuang Li, Jiangjie Chen, Siyu Yuan +4

To translate well, machine translation (MT) systems and general-purposed language models (LMs) need a deep understanding of both source and target languages and cultures. Therefore…

cs.CL2023★ 1 cited

Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models

Zhouhong Gu, Lin Zhang, Jiangjie Chen +8

Detectives frequently engage in information detection and reasoning simultaneously when making decisions across various cases, especially when confronted with a vast amount of info…