Beyond Logical Decomposition: Prioritizing Retrieval Actions in Multi-Hop QA

Multi-hop retrieval-augmented generation systems typically plan retrieval by the logical dependencies in a question, but logically valid retrieval actions can differ greatly in how much they narrow the search. We study this mismatch as the Search-Priority Gap: when several valid actions are available, current planners do not reliably start from the most selective one. To isolate this behavior, we construct 2,541 question pairs from 2WikiMultiHopQA by adding true but less selective facts about the bridge entity from Wikidata, while keeping the original identifying relation, the anchor, and thus the answer unchanged. Across decomposition-based, iterative, and agentic retrieval systems, these added facts cause substantial accuracy drops, e.g., from 67.1% to 31.0% for PlanRAG. The drop depends on which facts are added and on where the anchor appears in the question, even though its position does not change the problem. Trajectory analysis shows that added facts pull planners away from the anchor, so the bridge is found late or not at all. A simple few-shot prompt that prioritizes the anchor recovers part of the drop, raising AceSearcher-14B accuracy from 50.8% to 66.7%. These results suggest that multi-hop retrieval planning should account not only for logical dependency, but also for the retrieval priority of candidate actions.