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TomasuLLM is presented, a runtime that executes agent tool calls out of trajectory order while preserving task-execution correctness, and improves the reported benchmark means and scales with tool latency.
AgentZip is presented, the first memory compression system designed specifically for AI-agent sandboxes, which broadens the compression scope to any page with a profitable representation and shifts overhead control from compression-time page selection to restore-time prefetching.
To the authors' knowledge, this is the first empirical demonstration that an agent-driven hardware-design process can produce an RTL-practical prefetcher that outperforms state-of-the-art human designs on unseen workloads.
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