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Zhipeng Wang

المنشورات 6

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CARE: Certifying Acceleration for Vision-Language-Action Inference

Rui Liu, Tong Zheng, Jindong Gu وآخرون · 2026

While vision-language-action (VLA) models have advanced rapidly, running them at every control step remains expensive. Prior work accelerates VLA inference using techniques like action chunking and visual-token pruning, typically evaluating based on latency and average task success. However, acceleration may discard in …

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AvoKV-E: Payload-Aware KV Cache Eviction for Long Reasoning

Han Yu, Wenhui Zhu, Xiwen Chen وآخرون · 2026

Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely treat cached entries as routing objects, estimating whether an old key will still be read, will recur, or can be replaced. This routing-only view overlooks two effects: lo …

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SoK: Decentralized Agent Economic Infrastructure

Rui Sun, Xihan Xiong, Qin Wang وآخرون · 2026

Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately. This creates a simple problem: a workflow can look correct at each step and still produce the wrong outcome. For example, a correct escrow may release payment on an authorized approval that provides …

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SkelOT: Reusing AOT Compilation Across EVM Contract Families

Sipeng Xie, Qianhong Wu, Minghang Li وآخرون · 2026

Ahead-of-time (AOT) compilers (e.g., revmc, evmone, and DTVM) for the Ethereum Virtual Machine (EVM) reuse compilation artifacts at contract-code-hash granularity. This granularity is poorly matched to real EVM workloads dominated by \emph{contract families}: factory-, proxy-, and template-driven deployments that share …

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Embracing Flow Unsteadiness: A High-Throughput Learning Platform Enables Vortex-Exploiting Bioinspired Propulsion

Fei Han, Xinyu Cui, Zhipeng Wang وآخرون · 2026

Biological swimmers and flyers exploit unsteady vortices for propulsion, whereas engineered vehicles usually suppress them as disturbances. Learning such flow exploitation in machines is difficult because real-fluid interaction data are scarce and unstructured exploration is unstable in high-dimensional, history-depend …

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