الباحثون

Zihao Wang

المنشورات 6

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Reliability-aware short-term roll prediction for unmanned surface vehicles via multi-task learning and adaptive centralization

Kaizhen Li, Xi Zhou, Zihao Wang وآخرون · 2026

Reliable roll prediction of unmanned surface vehicles (USVs) is essential for ensuring navi?gational safety and enhancing autonomous decision-making. While existing studies primarily focus on improving prediction accuracy, the quantification of prediction reliability remains insufficiently addressed. To bridge this gap …

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Uni-VLaT: Whole-Body Tactile Adaptation of VLA Policies for Humanoid Loco-Manipulation

Zihao Wang, Shutong Liu, Siqi Zheng وآخرون · 2026

Physical contact often determines how a humanoid should respond during loco-manipulation, yet vision and proprioception alone are often insufficient to characterize physical interaction, especially when the contact region is occluded. Unlike sparse force or torque measurements at predefined regions, distributed tactile …

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SMAT: Simple and Efficient Merge-Aware Training

Yanggan Gu, Yuanyi Wang, Zhen Li وآخرون · 2026

Model merging integrates the capabilities of multiple experts without joint retraining, but standard expert training optimizes task loss alone and does not guarantee good performance after merging. Merge-aware training (MAT) aims to improve merged performance, but existing methods do not fully account for common mergin …

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Monet: Measuring the Ecosystem of Open-Source Text-to-Image Models Tailored for Harmful Services

The open-source text-to-image (T2I) ecosystem enables rapid model development and sharing, but also hosts models intentionally tailored for harmful services, which we call Monets. Prior work has examined specific types of harmful T2I models on individual platforms, but a Monet does not exist in isolation. The broader M …

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DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

DeepSeek-AI, Anyi Xu, B. Li وآخرون · 2026

The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation, prefill remains computationally expensive, and large KV caches continue to strain HBM and SSD capacity and data-transfer bandwidth. Togeth …

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