arXiv subjects

Yue Liang

Publications and source records attributed to Yue Liang.

7 recordsLinked to original sources

arXiv2026

FashionStylist: An Expert Knowledge-enhanced Multimodal Dataset for Fashion Understanding

Fashion understanding requires both visual perception and expert-level reasoning about style, occasion, compatibility, and outfit rationale. However, existing fashion datasets remain fragmented and task-specific, often focusing on item attributes, outfit co-occurrence, or weak textual supervision, and thus provide limited support for holistic outfit understanding. In this paper, we introduce FashionStylist, an expert-annotated benchmark for holistic and expert-level fashion understanding. Constructed through a dedicated fashion-expert annotation pipeline, FashionStylist provides professionally grounded annotations at both the item and outfit levels. It supports three representative tasks: outfit-to-item grounding, outfit completion, and outfit evaluation. These tasks cover realistic item recovery from complex outfits with layering and accessories, compatibility-aware composition beyond co-occurrence matching, and expert-level assessment of style, season, occasion, and overall coherence. Experimental results show that FashionStylist serves not only as a unified benchmark for multiple fashion tasks, but also as an effective training resource for improving grounding, completion, and outfit-level semantic evaluation in MLLM-based fashion systems.

cs.CV↗

arXiv2026

Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data

Inspired by behavioral science, we propose Behavior Learning (BL), a novel general-purpose machine learning framework that learns interpretable and identifiable optimization structures from data, ranging from single optimization problems to hierarchical compositions. It unifies predictive performance, intrinsic interpretability, and identifiability, with broad applicability to scientific domains involving optimization. BL parameterizes a compositional utility function built from intrinsically interpretable modular blocks, which induces a data distribution for prediction and generation. Each block represents and can be written in symbolic form as a utility maximization problem (UMP), a foundational paradigm in behavioral science and a universal framework of optimization. BL supports architectures ranging from a single UMP to hierarchical compositions, the latter modeling hierarchical optimization structures. Its smooth and monotone variant (IBL) guarantees identifiability. Theoretically, we establish the universal approximation property of BL, and analyze the M-estimation properties of IBL. Empirically, BL demonstrates strong predictive performance, intrinsic interpretability and scalability to high-dimensional data. Code: https://github.com/MoonYLiang/Behavior-Learning ; install via pip install blnetwork.

cs.LG↗

arXiv2026

CURVE: Learning Causality-Inspired Invariant Representations for Robust Scene Understanding via Uncertainty-Guided Regularization

Scene graphs provide structured abstractions for scene understanding, yet they often overfit to spurious correlations, severely hindering out-of-distribution generalization. To address this limitation, we propose CURVE, a causality-inspired framework that integrates variational uncertainty modeling with uncertainty-guided structural regularization to suppress high-variance, environment-specific relations. Specifically, we apply prototype-conditioned debiasing to disentangle invariant interaction dynamics from environment-dependent variations, promoting a sparse and domain-stable topology. Empirically, we evaluate CURVE in zero-shot transfer and low-data sim-to-real adaptation, verifying its ability to learn domain-stable sparse topologies and provide reliable uncertainty estimates to support risk prediction under distribution shifts.

cs.CV↗

arXiv2024

Ions-induced Epitaxial Growth of Perovskite Nanocomposites for Highly Efficient Light-Emitting Diodes with EQE Exceeding 30%

Metal halide perovskites, a class of cost-effective semiconductor materials, are of great interest for modern and upcoming display technologies that prioritize the light-emitting diodes (LEDs) with high efficiency and excellent color purity. The prevailing approach to achieving efficient luminescence from pervoskites is enhancing exciton binding effect and confining carriers by reducing their dimensionality or grain size. However, splitting pervoskite lattice into smaller ones generates abundant boundaries in solid films and results in more surface trap states, needing exact passivation to suppress trap-assisted nonradiative losses. Here, an ions-induced heteroepitaxial growth method is employed to assembe perovskite lattices with different structures into large-sized grains to produce lattice-anchored nanocomposites for efficient LEDs with high color purity. This approach enables the nanocomposite thin films, composed of three-dimensional (3D) CsPbBr3 and its variant of zero-dimensional (0D) Cs4PbBr6, to feature significant low trap-assisted nonradiative recombination, enhanced light out-coupling with a corrugated surface, and well-balanced charge carrier transport. Based on the resultant 3D/0D perovskite nanocomposites, we demonstrate the perovskite LEDs achieving an remarkable external quantum efficiency of 31.0% at the emission peak of 521 nm with a narrow full width at half-maximum of only 18 nm. This research introduces a novel approach to the development of well-assembled nanocomposites for perovskite LEDs, demonstrating high efficiency comparable to that of state-of-the-art organic LEDs.

cond-mat.mtrl-sci↗

arXiv2023

First sodium laser guide star asterism launching platform in China on 1.8m telescope at Gaomeigu Observatory

The application of sodium laser guide star is the key difference between modern adaptive optics system and traditional adaptive optics system. Especially in system like multi-conjugate adaptive optics, sodium laser guide star asterism which is formed by several laser guide stars in certain pattern is required to probe more atmospheric turbulence in different directions. To achieve this, a sodium laser guide star asterism launching platform is required. In this paper, we will introduce the sodium laser guide star asterism launching platform built and tested on the 1.8m telescope of the Gaomeigu Observatory. The platform has two functions: one is to compare the performance of sodium laser guide stars generated by different lasers at the same place; the other is to generate sodium laser guide star asterism with adjustable shape. The field test results at the beginning of 2021 verify the important role of the platform, which is also the first time to realize sodium laser guide star asterism in China.

astro-ph.IM↗

arXiv2021

Exact solution of the two-axis two-spin Hamiltonian

Bethe ansatz solution of the two-axis two-spin Hamiltonian is derived based on the Jordan-Schwinger boson realization of the SU(2) algebra. It is shown that the solution of the Bethe ansatz equations can be obtained as zeros of the related extended Heine-Stieltjes polynomials. Symmetry properties of excited levels of the system and zeros of the related extended Heine-Stieltjes polynomials are discussed. As an example of an application of the theory, the two equal spin case is studied in detail, which demonstrates that the levels in each band are symmetric with respect to the zero energy plane perpendicular to the level diagram and that excited states are always well entangled.

quant-ph↗

arXiv2021

Short term minutes-time scale temporal variation statistics of sodium layer dynamics

The brightness and height of the sodium laser guide star of adaptive optics could vary significantly due to the temporal dynamics of sodium column density and the mean height of sodium layer. To measure these dynamics, an independent sodium Lidar is a necessity. Without such an instrument, it is almost impossible to discern the cause of the brightness variation of laser guide star from the sodium layer's dynamics or other factors from the laser itself. For applications such as characterizing the performance of sodium laser for sodium laser guide star generation, minutes scale short term statistics of the sodium layers' abundance and height is extremely helpful for estimating the contribution of sodium layer's variation to the variation of laser guide star's brightness. In this paper, we analyzed our previous measurement of sodium layer dynamics that has been gathered in two winters, and presented the temporal variation statistics of sodium column density and mean height within minute time scale based on our measurements.

astro-ph.IM↗