pith:4MJVZM4R
iCoRe: An Iterative Correlation-Aware Retriever for Bug Reproduction Test Generation
An iterative retriever that tracks source-test differences, semantic-structural links, and generation feedback raises LLM success at producing bug reproduction tests.
arxiv:2604.19224 v2 · 2026-04-21 · cs.SE
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Claims
Experimental results show that our method achieves a Fail-to-Pass rate of 42.0% and 52.8% respectively, representing 19.7%-31.7% relative improvements over existing retrieval methods.
The three named correlations (source-test differentiation, semantic-structural relevance, retrieval-generation feedback) are the dominant factors limiting current retrievers and that an iterative loop will improve them without introducing new noise or instability in the LLM outputs.
iCoRe improves Fail-to-Pass rates to 42.0% and 52.8% on two bug reproduction benchmarks by using correlation-aware iterative retrieval instead of standard semantic or BM25 methods.
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| First computed | 2026-06-30T01:16:30.083384Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/4MJVZM4R3Q77C7P7U42BUTBUSH \
| jq -c '.canonical_record' \
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Canonical record JSON
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