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Zhe Liu

7 papers indexed

openalexSustainability2026-07-23

Digital Infrastructure and Manufacturing Supply Chain Capabilities: Evidence from China’s Pilot Cities

Weibo Jin, Yiming Wang, Zhe Liu, Shuang Wang, Xiaomin Yang

The reconfiguration of global value chains has raised concerns about the resilience and upgrading of manufacturing supply chains. This study examines whether digital infrastructure improves manufacturing supply chain capabilities, using the 2016 “Information for the People” pilot…

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openalexBuildings2026-07-23

Deep Learning-Based Aesthetic Perception of Spring Zone Street View Images: A Case Study of Jinan Mingfu City Area

Lin Chen, Li Liu, Zhe Liu

To address the existing gap in quantitative evaluation regarding the integrated visual effect of spring water landscapes and street spaces within Historical and Cultural Neighborhoods of Spring Zone, the Jinan Mingfu City area is selected as a typical case for this research. A qu…

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arxivcs.CV2026-07-15

CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference

Xu Li, Yi Zheng, Mengyang Zhao, Yuxuan Liang, Zhe Liu, Rui Zhu, et al.

Large Vision-Language Models (LVLMs) typically require processing hundreds to thousands of visual tokens, leading to substantial inference overhead. Existing visual token pruning methods either operate before the LLM using text-agnostic heuristics or prune inside the LLM at the c…

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arxivcs.CV2026-07-13

Read It Back: Pretrained MLLMs Are Zero-Shot Reward Models for Text-to-Image Generation

Runhui Huang, Qihui Zhang, Zhe Liu, Yu Gao, Jie Wu, Hengshuang Zhao

In this paper, we propose SpectraReward, a training-free reward function that turns pretrained MLLMs into off-the-shelf reward models for image-generation reinforcement learning. Instead of asking the MLLM to judge a generated image or answer decomposed verification questions, Sp…

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arxivcs.RO2026-07-05

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI

ACE-Brain Team, :, Ziyang Gong, Haoming Gu, Zehang Luo, Tianyi Zhang, et al.

Embodied AI is moving from isolated perception or action modules toward physical agents that understand, plan under goals, act through robot bodies, monitor progress, and improve from experience. Existing systems address this loop only in parts: end-to-end policies generate actio…

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arxiveess.SY2026-06-30

A Novel Method for Differential-Algebraic Dynamic Model Discovery in Power Systems: An LLM-Based Multi-Agent Collaborative Framework

Xinming Wang, Fan Tang, Yingli Wei, Yakun He, Zhe Liu, Ping Jiang, et al.

With large-scale integration of emerging power electronic devices represented by grid-forming inverters, power system dynamics increasingly exhibit strong nonlinearity, multi-timescale coupling, and black-box control logic. These features hinder conventional parameter identificat…

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arxivcs.AIcs.CV2026-06-25

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

Junwei Luo, Shuai Yuan, Zhenya Yang, Yansheng Li, Zhe Liu, Hengshuang Zhao

Earth Observation (EO) forecasting aims to predict future Earth surface dynamics from satellite observations under changing meteorological conditions. In this paper, we view this task as a partially observed, weather-driven world modeling problem, in which weather acts as a condi…

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