A fine-tuned Qwen3-Embedding model with contrastive learning outperforms baselines on bidirectional source-to-decompiled code association and generalizes to constant-algorithm tasks.
Cornstack: High-quality contrastive data for better code ranking
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
representative citing papers
Cross-lingual RACG shows non-trivial but unequal knowledge transfer across 13 programming languages, depending on linguistic affinity and pretraining diversity, with limited reliance on natural language information when using code-specific retrievers.
citing papers explorer
-
Identifier-Free Code Embedding Models for Scalable Search
A fine-tuned Qwen3-Embedding model with contrastive learning outperforms baselines on bidirectional source-to-decompiled code association and generalizes to constant-algorithm tasks.
-
Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Cross-lingual RACG shows non-trivial but unequal knowledge transfer across 13 programming languages, depending on linguistic affinity and pretraining diversity, with limited reliance on natural language information when using code-specific retrievers.