Yue Hu

LeMIP: Learning Mutually Incompatible Policies via determinantal diversity for zero-shot human-AI cooperation

Haotian Xu, Junjie Zeng, Qi Fang, Yue Hu et autres

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GeoNav: Empowering MLLMs with dual-scale geospatial reasoning for language-goal aerial navigation

Haotian Xu, Yue Hu, Chen Gao, Zhengqiu Zhu et autres

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SkipRIS: Skipping Redundant Tokens for Referring Image Segmentation

Liangtao Shi, Ting Liu, Zunnan Xu, Yue Hu et autres

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Energy survey and MATLAB/Simulink Simulation of 24VDC lighting systems for off-grid rural houses in Papua New Guinea

Sylvester Tirones, Yue Hu

Access to reliable electricity in rural Papua New Guinea remains limited. This has led to solutions involving solar PV and energy storage system to facilitates local energy demand in households. This study simulates and evaluates a 24?V DC lighting system integrating a …

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Unveiling the Impact of Data and Model Scaling on High-Level Control for Humanoid Robots

Yuxi Wei, Zirui Wang, Kangning Yin, Yue Hu et autres

Data scaling has long remained a critical bottleneck in robot learning. For humanoid robots, human videos and motion data are abundant and widely available, offering a free and large-scale data source. Besides, the semantics related to the motions enable modality alignment and …

High-Precision and High-Efficiency Trajectory Tracking for Excavators Based on Closed-Loop Dynamics

Ziqing Zou, Cong Wang, Yue Hu, Xiao Liu et autres

The complex nonlinear dynamics of hydraulic excavators, such as time delays and control coupling, pose significant challenges to achieving high-precision trajectory tracking. Traditional control methods often fall short in such applications due to their inability to effectively handle these nonlinearities, while commonly …

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NL2GenSym: Natural Language to Generative Symbolic Rules for SOAR Cognitive Architecture via Large Language Models

Junjie Zeng, Yue Hu, Zhengqiu Zhu, Quanjun Yin et autres

SOAR, a classic symbol-based cognitive architecture, has been fostering the development of general, human-like intelligent agents. Nevertheless, its practical adoption is hindered by the laborious manual rule coding. Emerging Large Language Models (LLMs) present the immense potential for efficient rules generation. However, …

UniOTalign: A Global Matching Framework for Protein Alignment via Optimal Transport

Yue Hu, Zanxia Cao

Protein sequence alignment is a cornerstone of bioinformatics, traditionally approached using dynamic programming (DP) algorithms that find an optimal sequential path. This paper introduces UniOTalign, a novel framework that recasts alignment from a fundamentally different perspective: global matching via Optimal Transport (OT). …

High-Precision and High-Efficiency Trajectory Tracking for Excavators Based on Closed-Loop Dynamics

Ziqing Zou, Cong Wang, Yue Hu, Xiao Liu et autres

The complex nonlinear dynamics of hydraulic excavators, such as time delays and control coupling, pose significant challenges to achieving high-precision trajectory tracking. Traditional control methods often fall short in such applications due to their inability to effectively handle these nonlinearities, while commonly …

SplitGround: Long-Chain Reasoning Split via Modular Multi-Expert Collaboration for Training-Free Scene Knowledge-Guided Visual Grounding

Yue Hu, Wansen Wu, Xinmeng Li, Quanjun Yin

Scene Knowledge-guided Visual Grounding (SK-VG) is a multi-modal detection task built upon conventional visual grounding (VG) for human–computer interaction scenarios. It utilizes an additional passage of scene knowledge apart from the image and context-dependent textual query for referred object localization. Due to …

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Research on time factor prediction in the Lee-Carter model—the combined model based on Lp-norm

Yue Hu, Wei Zhang, Ke Xu

For longevity risk, this paper focuses on accurately predicting mortality rates and proposes an improved time-factor prediction model to enhance the accuracy of mortality rate forecasting. Traditional time-factor model exhibits limitations in handling the nonlinearity and long memory characteristics. To overcome this, …

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Query Rephrasing for Context Independence in Scene Knowledge-guided Visual Grounding

Jing Ye, Haixiang Zhu, Wansen Wu, Yue Hu

Scene Knowledge-guided Visual Grounding (SK-VG) aims to locate the specific object in an image that is referred to by an open-ended query, utilizing textual scene knowledge for guidance. Besides the grounding ability, SK-VG models are expected to infer more information of the …

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