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cs.SE2026
Can Vision-Language Models Handle Long-Context Code? An Empirical Study on Visual Compression
Jianping Zhong, Guochang Li, Chen Zhi +6
Large Language Models (LLMs) struggle with long-context code due to window limitations. Existing textual code compression methods mitigate this via selective filtering but often di…
cs.SE2026
Better Call Grep: Evaluating and Improving Grep-Like Lexical Retrieval for Repository-Level Code Completion
Baoyi Wang, Xingliang Wang, Guochang Li +6
Repository-level code completion remains challenging for large language models (LLMs) due to cross-file dependencies and limited context windows. Prior work addresses this challeng…
cs.SE2025
Completion by Comprehension: Guiding Code Generation with Multi-Granularity Understanding
Xinkui Zhao, Rongkai Liu, Yifan Zhang +6
As code completion task from function-level to repository-level, leveraging contextual information from large-scale codebases becomes a core challenge. However, existing retrieval-…