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Jiang-Nan Yu

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#natural language process... Preprint Sep 2026

TomasuLLM: Out-of-Order Speculative Execution for LLM Agents

Long-running tools can dominate coding-agent latency: compilers, test suites, and repository commands take seconds to minutes while the agent idles. This observation stall presents the same tension that drove out-of-order processors -- asequential interface hides work that can be predicted and started early, but a spec...

Jiang-Nan Yu, Ce-Yu Xu, Meng-Ming Li et al. · 0 citations
#machine learning Preprint Sep 2026

EfficientAgent: What Makes KV Cache Offloading Work for Concurrent Agents?

LLM agents resend their whole conversation on every turn, and most of it was already processed on the previous turn. Serving systems avoid recomputing it by caching its key-value (KV) state and, when GPU memory runs out, by offloading that state to host memory. For agents, offloading gives inconsistent results: on the...

Kun-Ming Shao, Jie-Run Chen, Jiang-Nan Yu et al. · 0 citations

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