A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling
3.60T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2607.07666.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA multi-agent framework called Ensemble QSP uses a three-layer hierarchical memory that keeps injected context bounded (median 301 tokens, max 4,050 across 104 runs). Five specialist worker agents operate under domain-expert principal investigators for autonomous pharmacokinetic-pharmacodynamic modeling, with benchmarks showing improved PK parameter recovery over single-agent baselines.
Why it mattersConcrete token-budget numbers and a domain-agnostic agent structure make the bounded-context design transferable to other long-horizon multi-agent setups beyond pharmacology.
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