Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks

ArXi:2511.10465v2 Announce Type: replace-cross While prompt optimization has emerged as a critical technique for enhancing language model performance, existing approaches primarily focus on elicitation-based strategies that search for optimal prompts to activate models' capabilities. These methods exhibit fundamental limitations when addressing knowledge-intensive tasks, as they operate within static knowledge capacity rather than providing the factual knowledge, terminology precision, and reasoning patterns required in specialized domains.