DIPS fine-tunes LLMs to output ordered feasible decision vectors approximating Pareto fronts for constrained bi-objective convex problems, reaching 95-98% normalized hypervolume with 0.16s inference.
IEEE Trans
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
Proposes an exploratory diagnostic workflow to highlight behavioral variation along MORL Pareto fronts not captured by objective values, with validation on grid and continuous control tasks.
An evolutionary search framework auto-configures multi-scale bi-branch CNNs to generate Pareto fronts of error-versus-complexity models for multi-output time-series forecasting.
A replicator-type dynamic on the standard simplex for feature weights from a normalized data matrix converges globally to a unique interior equilibrium.
citing papers explorer
-
Feature weighting for data analysis via evolutionary simulation
A replicator-type dynamic on the standard simplex for feature weights from a normalized data matrix converges globally to a unique interior equilibrium.