CLSA
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Code Lifespan Survival Analysis (CLSA): Predicting the Survival of Source Code Lines Using AST-Aware Mining
arXiv:2606.04993v1 Announce Type: new Abstract: Context: Predicting which source lines will be deleted - and when - matters for maintenance, technical debt, and review prioritization. Existing MSR approaches work at file or method granularity, masking individual-statement risk. Objective: We introduce Code Lifespan Survival Analysis (CLSA), the first framework to model code survival at individual-line granularity.
You Only Index Once: Cross-Layer Sparse Attention with Shared Routing
Announce Type: new Abstract: Long-context inference in modern LLMs is increasingly constrained by decoding efficiency, especially in reasoning-heavy settings where models generate long intermediate chains of thought. Existing sparse attention methods often face a practical efficiency-quality trade-off. Structured block sparse methods typically provide stronger acceleration but incur noticeable quality loss, while token sparse methods are usually more accurate yet deliver limited end-to-end...
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