Abstract: Multimodal multiobjective optimization aims to provide diversified acceptable decisions (ADs), including GOS with consistent objective evaluations and local optimal solutions (LOSs) with ...
LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.