A co-evolutionary method evolves LLM prompts and circuits to produce 8-bit approximate multipliers with better error-area trade-offs than EvoApproxLib.
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Pith papers citing it
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cs.NE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A data-driven framework applies population-based bio-inspired algorithms to recalibrate and evolve a prostate cancer-specific comorbidities index, reporting up to 0.1 improvement in concordance index over the Charlson index.
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Multi-Objective Coevolution of Prompts and Templates for Circuit Approximation
A co-evolutionary method evolves LLM prompts and circuits to produce 8-bit approximate multipliers with better error-area trade-offs than EvoApproxLib.
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Developing a novel Comorbidities Index for predicting 10-year mortality in Prostate Cancer patients: A computational data-driven approach
A data-driven framework applies population-based bio-inspired algorithms to recalibrate and evolve a prostate cancer-specific comorbidities index, reporting up to 0.1 improvement in concordance index over the Charlson index.