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Hao Wu

14 papers indexed

openalexFrontiers in Immunology2026-07-24

Non-redundant functions of NFATc1 in survival and NFATc2 in generation of exhausted CD8+ T cells

Salvador Sampere-Birlanga, Stefan Klein‐Hessling, Miriam Campillo Prados, Anfei Huang, Hao Wu, Andreas Rosenwald, et al.

Persistent antigenic stimulation leads to the dysfunction of CD8 + cytotoxic T cells. These “exhausted” T EX cells exhibit reduced proliferative capacity, impaired effector function, and increased expression of co-inhibitory receptors. Chronic antigen receptor stimulation induces…

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arxivcs.CV2026-07-21

GATE-3D: Geometry-Aware Test-time Adaptive Reranking for Open-Set 3D Shape Retrieval

Hao Wu, Heyi Lin, Zilin Wang, Huizai Yao, Hao Wang, Hui Xiong

Large pretrained vision models have substantially improved appearance-based 3D shape retrieval, but they still confuse shapes that look similar while differing in geometry. Although geometry-aware features can reduce these errors, naive fusion of geometry and appearance may hurt…

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arxivcs.CV2026-07-21

CR-Refiner: An Object-Centric Optimal Transport Reranker for Edit-Conditioned 3D Scene Retrieval

Hao Wu, Jinjing Zhu, Nanyu Wu, Qianyi Cai, Heyi Lin, Hao Wang, et al.

Edit-conditioned 3D scene retrieval pairs a reference 3D room with a natural-language modification and retrieves rooms from a corpus that satisfy the edit. Three lines of prior work each fall short on this task. 2D composed image retrieval reasons over pixel-level edits and has n…

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arxivcs.CVcs.AIcs.CL2026-07-20

Thinking in Video: Can Video Generators Really Reason About the Real World?

Yongheng Zhang, Guang Yang, Ruihan Hou, Qiguang Chen, Ziang Liu, Xiaolong Liu, et al.

Recent advances in world models and video generation have given rise to an emerging reasoning paradigm that leverages video generative models to simulate, predict, and reason about real-world dynamics. We redefine this paradigm as Thinking in Video, where video is not merely an o…

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arxivcs.AI2026-07-17

SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery

SciForge Team, Zhangyang Gao, Minghao Fang, Yifei Liu, Hanhui Yang, Xinyu Gu, et al.

Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet general-purpose AI assistants rarely preserve these objects as a coherent, auditable research state. We pr…

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arxivcs.CV2026-07-17

IoUPD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models

Xiuyuan Zhu, Ke Lu, Hao Wu, Zijin Du, Dongming Zhang, Jian Xue

Visual grounding with multimodal large language models is commonly formulated as autoregressive coordinate generation, where a model outputs bounding-box coordinates as text given an image and a referring-expression prompt. While this interface is simple and compatible with instr…

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arxivcs.LGcs.AI2026-07-13

SOAP, Muon, and Beyond: Pushing LLM Pretraining Scales

Mikail Khona, Aditya Vavre, Boxiang Wang, Deyu Fu, Hao Wu, Mike Chrzanowski, et al.

Higher-order optimizers such as Muon and SOAP offer faster convergence than AdamW, but their computational cost and numerical stability challenges have limited adoption at scale. In this work, we adapt and enhance preconditioned gradient methods to overcome the practical challeng…

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arxiveess.SP2026-07-11

Low-Altitude ISAC With Spherical Directly-Connected Antenna Array: Performance Analysis and Beamforming Optimization

Zhiqiang Xiao, Tao Zhang, Zhenjun Dong, Hao Wu, Xiaoqiang Qiao, Jianhua Zhang

The safety development requirements of low-altitude economy (LAE) renders the robust low-altitude airspace monitoring critical important than ever before. Integrated sensing and communication (ISAC) as one of the key development trends of 6G provides potential solutions for the L…

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arxivcs.ROcs.CVcs.OS2026-07-02

Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots

Ling Xu, Chuyu Han, Borui Li, Hao Wu, Shiqi Jiang, Ting Cao, et al.

Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model-specific Python stacks, backend assumptions, and robot-side glue code, especially on heterogeneous edge devices. Existing infer…

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arxivcs.AIcs.CR2026-07-01

HARC: Coupling Harmfulness and Refusal Directions for Robust Safety Alignment

Shei Pern Chua, Hao Wu, Qianli Ma, Fangzhao Wu

Understanding how aligned LLMs internally represent safety is critical for diagnosing alignment vulnerabilities, as it explains why jailbreaks succeed and informs the design of robust alignment strategies. Prior work shows that aligned LLMs encode harmfulness and refusal as separ…

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crossrefAdvances in Transdisciplinary Engineering2026-06-19

A Dynamic Bayesian Network–Based Method for Real-Time Modeling of Communication Behaviors in Medical Internet of Things

Yu Zhang, Zhiyong Hu, Jianjun Xue, Keng Li, Ming Xue, Jingjing Ren, et al.

The rapid proliferation of the Medical Internet of Things (MIoT) has significantly enhanced real-time healthcare monitoring while introducing complex, dynamic communication behaviors among heterogeneous medical devices. Accurate modeling of these behaviors is essential for ensuri…

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crossrefSymmetry2019-11-08Cited by 28

Internet of Things Meets Vehicles: Sheltering In-Vehicle Network through Lightweight Machine Learning

Junchao Xiao, Hao Wu, Xiangxue Li

An internet of vehicles allows intelligent automobiles to interchange messages with other cars, traffic management departments, and data analysis companies about vehicle identification, accident detection, and danger warnings. The implementation of these features requires Interne…

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