arXiv subjects

Yuxi Tian

Publications and source records attributed to Yuxi Tian.

5 recordsLinked to original sources

arXiv2026

CAD 100K: A Comprehensive Multi-Task Dataset for Car Related Visual Anomaly Detection

Multi-task visual anomaly detection is critical for car-related manufacturing quality assessment. However, existing methods remain task-specific, hindered by the absence of a unified benchmark for multi-task evaluation. To fill in this gap, We present the CAD Dataset, a large-scale and comprehensive benchmark designed for car-related multi-task visual anomaly detection. The dataset contains over 100 images crossing 7 vehicle domains and 3 tasks, providing models a comprehensive view for car-related anomaly detection. It is the first car-related anomaly dataset specialized for multi-task learning(MTL), while combining synthesis data augmentation for few-shot anomaly images. We implement a multi-task baseline and conduct extensive empirical studies. Results show MTL promotes task interaction and knowledge transfer, while also exposing challenging conflicts between tasks. The CAD dataset serves as a standardized platform to drive future advances in car-related multi-task visual anomaly detection.

cs.CV↗

arXiv2026

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis

The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently, anomaly synthesis techniques have been developed to enlarge training sets and enhance downstream inspection. However, existing methods either suffer from poor integration caused by inpainting or fail to provide accurate masks. To address these limitations, we propose GroundingAnomaly, a novel few-shot anomaly image generation framework. Our framework introduces a Spatial Conditioning Module that leverages per-pixel semantic maps to enable precise spatial control over the synthesized anomalies. Furthermore, a Gated Self-Attention Module is designed to inject conditioning tokens into a frozen U-Net via gated attention layers. This carefully preserves pretrained priors while ensuring stable few-shot adaptation. Extensive evaluations on the MVTec AD and VisA datasets demonstrate that GroundingAnomaly generates high-quality anomalies and achieves state-of-the-art performance across multiple downstream tasks, including anomaly detection, segmentation, and instance-level detection.

cs.CV↗

arXiv2026

Colloidal Nanocrystals Regrowth-Assisted Synthesis of Perovskite Microwire Lasers for Integrated Optoelectronics

Colloidal perovskite nanocrystals (NCs) are a well-proven platform for growing anisotropic structures. Nanowires (NWs) exhibiting a quantum confinement phenomenon and microwires (MWs), which enable lasing, are of particular interest for optoelectronic devices. Synthesis of the latter is challenging. Herein, we report a straightforward access to high-quality CsPbBr3 MW lasers. We utilize a diphenyl ether (DPE) solvent for the hot-injection synthesis. DPE coordinates strongly to Pb2+ and allows to reduce an excess of oleic acid/oleylamine ligand pair well established for PbBr2 dissolution and inhibition of as-formed NCs regrowth. Therefore, a rapid injection of Cs-oleate into the PbBr2-containing solution yields lead-depleted Cs4PbBr6 NCs which slowly release perovskite precursors and produce CsPbBr3 counterparts. The latter transform into NWs through an oriented-attachment mechanism, which in turn evolve into laser MWs. To demonstrate spectrally tunable lasing in MWs we employ YCl3 for ion exchange in perovskite lattice. Resultant CsPb(Cl,Br)3 MWs show high-Q coherent emission in the 485-540 nm range. To highlight the potential of synthesized MWs for integrated optoelectronics, we assemble a device comprising a CsPb(Cl,Br)3 MW laser coupled to MoO3 lossless nanowaveguide, which delivers coherent light to a CsPbBr3 MW photodetector. The device exhibits a nonlinear optoelectronic response applicable for on-chip neuromorphic computing.

physics.optics↗

arXiv2024

Evaluating the impact of instrumental variables in propensity score models using synthetic and negative control experiments

In pharmacoepidemiology research, instrumental variables (IVs) are variables that strongly predict treatment but have no causal effect on the outcome of interest except through the treatment. There remain concerns about the inclusion of IVs in propensity score (PS) models amplifying estimation bias and reducing precision. Some PS modeling approaches attempt to address the potential effects of IVs, including selecting only covariates for the PS model that are strongly associated to the outcome of interest, thus screening out IVs. We conduct a study utilizing simulations and negative control experiments to evaluate the effect of IVs on PS model performance and to uncover best PS practices for real-world studies. We find that simulated IVs have a weak effect on bias and precision in both simulations and negative control experiments based on real-world data. In simulation experiments, PS methods that utilize outcome data, including the high-dimensional propensity score, produce the least estimation bias. However, in real-world settings underlying causal structures are unknown, and negative control experiments can illustrate a PS model's ability to minimize systematic bias. We find that large-scale, regularized regression based PS models in this case provide the most centered negative control distributions, suggesting superior performance in real-world scenarios.

stat.ME↗

arXiv2023

Unraveling Intertwined Impacts between Lattice Vacancy and Substrate on Photonic Quasiparticles in Monolayer MoS$_2$

Lattice defects and interfacial absorbates represent two extrinsic but ubiquitous factors that exert profound impacts on the luminescent properties of semiconductors. However, their impacts are normally tangled and remain to be separately elucidated. Here, we clarify the individual roles of each factor by tracking the weight evolution of photonic quasiparticles by modulating the densities of sulfur vacancies in monolayer MoS$_2$ via ad hoc defect engineering. In particular, we perform atomistic analyses on the densities of sulfur vacancies by employing atomically resolved scanning transmission electron microscopy to quantitatively characterize the generation rates of sulfur vacancies in MoS$_2$ on two types of substrates with opposite surface hydrophobicity natures. We reveal that the generation rate of sulfur vacancies can even double on the hydrophilic substrates. More importantly, the impact of sulfur vacancies over the weight of trionic emission is closely associated with the substrate hydrophobicity, which is manifested noticeably in the hydrophobic substrates, but insignificant in the hydrophilic ones. The results represent an in-depth understanding on the roles of the extrinsic factors on the luminescent properties in atomically thin semiconductors.

cond-mat.mtrl-sci↗