Finding specific preference-guided Pareto solutions that represent different tradeoffs among multiple objectives is critical yet challenging in multi-objective problems. Existing methods are restrictive in preference definitions and/or their theoretical guarantees.

Species range maps (SRMs) are essential tools for research and policy-making in ecology, conservation, and environmental management.

Large language models (LLMs) have shown impressive performance on downstream tasks by in-context learning (ICL), which heavily relies on the quality of demonstrations selected from a large set of annotated examples.