activity
20222024
most citedKnowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

31 citations · 52 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL20243 cited

Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models

Zhuo Chen, Jiawei Liu, Haotan Liu +4

Retrieval-Augmented Generation (RAG) is applied to solve hallucination problems and real-time constraints of large language models, but it also induces vulnerabilities against retr…

cs.CV2024

UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weather

Haimei Zhao, Jing Zhang, Zhuo Chen +2

LiDAR semantic segmentation (LSS) is a critical task in autonomous driving and has achieved promising progress. However, prior LSS methods are conventionally investigated and evalu…

cs.CL20241 cited

Using Interpretation Methods for Model Enhancement

Zhuo Chen, Chengyue Jiang, Kewei Tu

In the age of neural natural language processing, there are plenty of works trying to derive interpretations of neural models. Intuitively, when gold rationales exist during traini…

cs.CL20243 cited

Self-Improvement Programming for Temporal Knowledge Graph Question Answering

Zhuo Chen, Zhao Zhang, Zixuan Li +4

Temporal Knowledge Graph Question Answering (TKGQA) aims to answer questions with temporal intent over Temporal Knowledge Graphs (TKGs). The core challenge of this task lies in und…

cs.AI202431 cited

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

Zhuo Chen, Yichi Zhang, Yin Fang +12

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the semantic web community's exploration into multi-modal dimensions unlocking new avenues for…

cs.AI20247 cited

Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion

Yichi Zhang, Zhuo Chen, Lei Liang +2

Multi-modal knowledge graph completion (MMKGC) aims to predict the missing triples in the multi-modal knowledge graphs by incorporating structural, visual, and textual information…