BACE reformulates LLM code synthesis as Bayesian co-evolution of code and test populations anchored on minimal public examples, achieving superior performance on LiveCodeBench v6.
DOI 10.48550/arXiv.2502.10802
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Analysis of SATD in Dockerfiles shows 27% of admissions and 40% of repayments are coupled to non-Dockerfile artifacts, with coupled events repaid faster overall and external dependencies as a key trigger.
TRACE aggregates answer consistency and confidence trajectory over multiple reasoning steps to decide when to halt inference, reducing token usage by 25-30% while keeping accuracy within 1-2% of full reasoning.
citing papers explorer
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BACE: LLM-based Code Generation through Bayesian Anchored Co-Evolution of Code and Test Populations
BACE reformulates LLM code synthesis as Bayesian co-evolution of code and test populations anchored on minimal public examples, achieving superior performance on LiveCodeBench v6.
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Beyond the Tip of the Iceberg: Understanding SATD in Dockerfiles through the Lens of Co-evolution
Analysis of SATD in Dockerfiles shows 27% of admissions and 40% of repayments are coupled to non-Dockerfile artifacts, with coupled events repaid faster overall and external dependencies as a key trigger.
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Efficient Test-Time Scaling via Temporal Reasoning Aggregation
TRACE aggregates answer consistency and confidence trajectory over multiple reasoning steps to decide when to halt inference, reducing token usage by 25-30% while keeping accuracy within 1-2% of full reasoning.