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Diffusion models can now achieve one-step, efficient action generation for online multi-agent coordination, shattering previous scalability barriers.
Decades of hand-crafted heuristics for counting and sampling constrained binary matrices can be replaced by a single amortized GFlowNet that achieves a 99.8% median effective sample fraction across unseen margins.
This work shows that the frozen agent LLM already carries the routing signal in its own forward passes, and that two linear maps suffice to read it out with no skill text in the context, and shows that Gavel (Glance And Verdict from a frozen LLM) reads it in two steps.
A novel safe task-planning framework, SafeMem, which constructs and maintains a long-term semantic graph memory of the open and dynamic environment, and substantially improves safe success rates compared to state-of-the-art VLM-driven task planners.
Skill selection in LLMs can be optimized to achieve a 0.73 task success rate while using 28% fewer tokens than existing methods.
