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Latent reasoning enables vision-language-action (VLA) models to transform multimodal observations into task-relevant internal states before generating continuous robot actions. While existing methods learn to generate or refine such states for each policy query, they discard successful reasoning after execution and the...
Complex tasks inherently couple workflow structure, agent responsibility, collaboration, and memory access: task regions delimit responsibility and tool scope, cross-region dependencies give rise to handoffs, and ownership boundaries delimit private and selectively shared memory. Existing methods can jointly optimize a...
CoMemBench is introduced, an execution-grounded benchmark for collaborative memory sharing and isolation across multi-agent workflow topologies, and reveals a sharing-isolation trade-off: broader context improves information availability but can weaken isolation, while system rankings shift across topologies and artifa...
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