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HM-Router is introduced, a routing method that jointly selects a model and harness for each query, with an interaction term inspired by canonical polyadic tensor decomposition to capture how their compatibility varies with the query.
Metro-WM is introduced, a hierarchical framework that issues sub-goals by retrieving genuine states from prior experience rather than generating ungrounded latent vectors that achieves superior long-horizon success rates and maintains robust performance under extremely sparse dataset conditions.
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