IRM
IRM is the trainable retrieval mechanism in the PNSN architecture. Through indexing and parametric selection, it matches the most relevant parameter set to an input query, replacing fixed-rule routing.
Timeline (last 90 days)
PNSN uses an index and a trainable retrieval mechanism (IRM) to select the most relevant parameter sets to participate in computation.
The identity-transform baseline is a routing strategy that does no learning at all; IRM directly returns the raw representation of the query itself or a fixed mapping.
In the evaluation with seven held-out queries, the trained IRM achieved 4/7 correct on top-1 results, versus 3/7 for the identity-transform baseline.
On the identity-related subset, IRM achieved 3/5 correct, versus 1/5 for the identity-transform baseline.
All Facts (4)
PNSN uses an index and a trainable retrieval mechanism (IRM) to select the most relevant parameter sets to participate in computation.
50%UnverifiedThe identity-transform baseline is a routing strategy that does no learning at all; IRM directly returns the raw representation of the query itself or a fixed mapping.
50%UnverifiedIn the evaluation with seven held-out queries, the trained IRM achieved 4/7 correct on top-1 results, versus 3/7 for the identity-transform baseline.
50%UnverifiedOn the identity-related subset, IRM achieved 3/5 correct, versus 1/5 for the identity-transform baseline.
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