HIERA: Hierarchical Multi-Agent Relevance Assessment for Content Discovery Systems
3.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.00785.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryHIERA is a hierarchical multi-agent framework for automated relevance assessment in content discovery. Four specialized agents (Relevance Judge, Query Analyzer, Item Analyzer, Relation Analyzer) coordinate hierarchically rather than via flat voting or uncoordinated aggregation. Ablations show the coordination structure itself drives performance gains of up to 38% over 11 baselines across five datasets.
Why it mattersA primary-source ablation isolates hierarchical coordination as the causal driver of multi-agent gains, distinct from the agents or external knowledge themselves. Useful architectural evidence for pipeline design.
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