logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

Provide explainable clues: A generative traceable method for knowledge graph completion

delete2025-09-12
delete0
PRE
AI
Z
Ziqi Ma
J
Jinpeng Li
H
Hang Yu
DOI：10.1016/j.knosys.2025.114426delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
• Provide explainability clues for generative models. • Analyze the rationality of the clues. • Guide the accuracy of the generative model’s reasoning.

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

Organization

N
national deep sea center
Scholars:
35
Papers: 26
Citations: 0
S
shanghai university
Scholars:
3.9W
Papers: 2.7W
Citations: 52