Stale repository context in code RAG actively induces models to produce obsolete helper references, raising stale outputs by 76-88 percentage points over current-only retrieval in a 17-sample diagnostic study.
31 Technical Report Di Wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, and Xiaofei Ma
6 Pith papers cite this work. Polarity classification is still indexing.
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ALADDIN is a user-requirement-driven GUI test generation framework that incrementally navigates mobile app UIs and builds LLM-guided oracles to validate both correct and faulty user-requested functionalities across six apps.
Introduces OCR+PAGE-1 and OCR+PAGE-N prompting strategies that improve zero-shot multi-page handwritten document transcription by sharing context across pages.
Function-based chunking underperforms other strategies in RAG code completion by 3.57-5.64 points, with context length as the dominant factor.
Qwen2.5-Coder models claim state-of-the-art results on over 10 code benchmarks, outperforming larger models of similar size.
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.
citing papers explorer
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When Retrieval Hurts Code Completion: A Diagnostic Study of Stale Repository Context
Stale repository context in code RAG actively induces models to produce obsolete helper references, raising stale outputs by 76-88 percentage points over current-only retrieval in a 17-sample diagnostic study.
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Automated Functional Testing for Malleable Mobile Application Driven from User Intent
ALADDIN is a user-requirement-driven GUI test generation framework that incrementally navigates mobile app UIs and builds LLM-guided oracles to validate both correct and faulty user-requested functionalities across six apps.
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Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription
Introduces OCR+PAGE-1 and OCR+PAGE-N prompting strategies that improve zero-shot multi-page handwritten document transcription by sharing context across pages.
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How Does Chunking Affect Retrieval-Augmented Code Completion? A Controlled Empirical Study
Function-based chunking underperforms other strategies in RAG code completion by 3.57-5.64 points, with context length as the dominant factor.
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Qwen2.5-Coder Technical Report
Qwen2.5-Coder models claim state-of-the-art results on over 10 code benchmarks, outperforming larger models of similar size.
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A Survey on Large Language Models for Code Generation
A systematic literature review that organizes recent work on LLMs for code generation into a taxonomy covering data curation, model advances, evaluations, ethics, environmental impact, and applications, with benchmark comparisons.