A subgoal memory graph helps GUI agents reuse meaningful pieces of experience
The method stores reusable subgoal experiences between the granularity of single actions and complete task histories.
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The method stores reusable subgoal experiences between the granularity of single actions and complete task histories.
A candidate-valuation module aims to reduce target-model work while preserving greedy decoding output.
Formal supervisory control models capabilities, approvals and budgets, while accounting for the cost of refused actions.
A lightweight steering adapter aims to vary instruction adherence while preserving fluent responses.
Runtime routing chooses between primitive actions and larger skills, with explicit recovery when a macro does not fit.
An asynchronous framework routes difficult questions to agents that exchange intermediate findings through a shared buffer.
Conservative Meta-Agent Search evaluates architecture changes with replay, risk checks, a simulated canary and rollback.
A research framework combines preference learning, fair allocation and explicit dietary-rule filtering for households.
A training-free evaluation method compares history-conditioned expectations with observed video windows.
A framework defines research-integrity failures, detects them after a run and intervenes during execution.
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