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Improving code completion interpretability with concept-level intervention

delete2026-09-04
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PRE
AI
K
Kongyi Fan *
Z
Zongwen Shen
Y
Y. Li
陈翔 cover
陈翔 (Xiang Chen) *
Y
Yulin Zhuang
J
Jidong Ge *
B
Bin Luo
DOI:10.1016/j.infsof.2026.108309delete
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Abstract

Abstract

En 中文
Code pre-trained models have been widely adopted in automated code completion tasks. However, traditional completion approaches primarily rely on sequential modeling, which often overlooks the rich syntactic and structural information inherent in source code.

Journal

Information and Software Technology cover
Information and Software Technology
IF:
4.3
Papers:
3.8K
Citations:
7.7K

Organization

N
nantong university
Scholars:
4.3K
Papers: 1.3K
Citations: 0
N
nanjing university
Scholars:
7.8W
Papers: 5.6W
Citations: 87
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