Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment

arXiv:2402.19085v1 Announce Type: cross
Abstract: Alignment in artificial intelligence pursues the consistency between model responses and human preferences as well as values. In practice, the multifaceted nature of human preferences inadvertently introduces what is known as the "alignment tax" -a compromise where enhancements in alignment within one objective (e.g.,harmlessness) can diminish performance in others (e.g.,helpfulness). However, existing alignment techniques are mostly unidirectional, leading to suboptimal trade-offs and poor flexibility over various objectives. To navigate this challenge, we argue the prominence …

abstract alignment artificial artificial intelligence arxiv cs.ai cs.cl cs.sy eess.sy human intelligence multi-objective nature optimization performance practice responses tax type values