arXiv subjects

Yilan Jiang

Publications and source records attributed to Yilan Jiang.

5 recordsLinked to original sources

arXiv2026

Data-Induced Groupings and How To Find Them

Making sense of a visualization requires the reader to consider both the visualization design and the underlying data values. Existing work in the visualization community has largely considered affordances driven by visualization design elements, such as color or chart type, but how visual design interacts with data values to impact interpretation and reasoning has remained under-explored. Dot plots and bar graphs are commonly used to help users identify groups of points that form trends and clusters, but are liable to manifest groupings that are artifacts of spatial arrangement rather than inherent patterns in the data itself. These ``Data-induced Groups'' can drive suboptimal data comparisons and potentially lead the user to incorrect conclusions. We conduct two user studies using dot plots as a case study to understand the prevalence of data-induced groupings. We find that users rely on data-induced groupings in both conditions despite the fact that trend-based groupings are irrelevant in nominal data. Based on the study results, we build a model to predict whether users are likely to perceive a given set of dot plot points as a group. We discuss two use cases illustrating how the model can assist visualization designers by both diagnosing potential user-perceived groupings in dot plots and offering redesigns that better accentuate desired groupings through data rearrangement.

cs.HC↗

arXiv2025

ShortageSim: Simulating Drug Shortages under Information Asymmetry

Drug shortages pose critical risks to patient care and healthcare systems worldwide, yet the effectiveness of regulatory interventions remains poorly understood due to information asymmetries in pharmaceutical supply chains. We propose \textbf{ShortageSim}, addresses this challenge by providing the first simulation framework that evaluates the impact of regulatory interventions on competition dynamics under information asymmetry. Using Large Language Model (LLM)-based agents, the framework models the strategic decisions of drug manufacturers and institutional buyers, in response to shortage alerts given by the regulatory agency. Unlike traditional game theory models that assume perfect rationality and complete information, ShortageSim simulates heterogeneous interpretations on regulatory announcements and the resulting decisions. Experiments on self-processed dataset of historical shortage events show that ShortageSim reduces the resolution lag for production disruption cases by up to 84\%, achieving closer alignment to real-world trajectories than the zero-shot baseline. Our framework confirms the effect of regulatory alert in addressing shortages and introduces a new method for understanding competition in multi-stage environments under uncertainty. We open-source ShortageSim and a dataset of 2,925 FDA shortage events, providing a novel framework for future research on policy design and testing in supply chains under information asymmetry.

cs.MA↗

arXiv2025

Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs

Modern engineering, spanning electrical, mechanical, aerospace, civil, and computer disciplines, stands as a cornerstone of human civilization and the foundation of our society. However, engineering design poses a fundamentally different challenge for large language models (LLMs) compared with traditional textbook-style problem solving or factual question answering. Although existing benchmarks have driven progress in areas such as language understanding, code synthesis, and scientific problem solving, real-world engineering design demands the synthesis of domain knowledge, navigation of complex trade-offs, and management of the tedious processes that consume much of practicing engineers' time. Despite these shared challenges across engineering disciplines, no benchmark currently captures the unique demands of engineering design work. In this work, we introduce EngDesign, an Engineering Design benchmark that evaluates LLMs' abilities to perform practical design tasks across nine engineering domains. Unlike existing benchmarks that focus on factual recall or question answering, EngDesign uniquely emphasizes LLMs' ability to synthesize domain knowledge, reason under constraints, and generate functional, objective-oriented engineering designs. Each task in EngDesign represents a real-world engineering design problem, accompanied by a detailed task description specifying design goals, constraints, and performance requirements. EngDesign pioneers a simulation-based evaluation paradigm that moves beyond textbook knowledge to assess genuine engineering design capabilities and shifts evaluation from static answer checking to dynamic, simulation-driven functional verification, marking a crucial step toward realizing the vision of engineering Artificial General Intelligence (AGI).

cs.CE↗

arXiv2025

Reconfigurable Room Temperature Exchange Bias through N\'eel Order Switching in van der Waals Heterostructures

Exchange bias effect plays a crucial role in modern magnetic memory technology. Recently, van der Waals magnetic materials have emerged and shown potential in spintronic devices at atomic scale. Owing to their tunable physical properties and the flexibility in fabrication, the van der Waals heterostructures offer more possibilities for investigating potential mechanisms of the exchange bias effect. However, due to low magnetic ordering temperatures for most van der Waals magnets, to establish exchange bias in van der Waals antiferromagnet/ferromagnet heterostructures at room temperature is challenging. In this study, we fabricate (Fe$_{0.56}$Co$_{0.44}$)$_{5}$GeTe$_{2}$(FCGT)/Fe$_{3}$GaTe$_{2}$(FGaT) heterostructures with magnetic ordering temperatures of each component well above room temperature to achieve a room temperature exchange bias effect. It is found that the sign and magnitude of the exchange bias field can be efficiently controlled by manipulating the N\'eel order of FCGT with magnetic field. The manipulation of N\'eel order shows significant magnetic field dependence. A strong pre-set field induces a switch in the N\'eel order of FCGT, which aligns the interfacial magnetization at the FCGT/FGaT interface, leading to robust exchange bias, as revealed by both transport measurements and macro-spin model calculations. Our findings demonstrate the intrinsic manipulation and switchable of room-temperature exchange bias in all-van der Waals heterostructures and further promote the development of novel two-dimensional spintronic devices.

cond-mat.mtrl-sci↗

arXiv2024

Roles of the Narrow Electronic Band near the Fermi Level in 1T-TaS$_2$-Related Layered Materials

Here we use low-temperature scanning tunneling microscopy and spectroscopy (STM/STS) to reveal the roles of the narrow electronic band in two 1T-TaS$_2$-related materials (bulk 1T-TaS$_2$ and 4Hb-TaS$_2$). 4Hb-TaS$_2$ is a superconducting compound with alternating 1T-TaS$_2$ and 1H-TaS$_2$ layers, where the 1H-TaS$_2$ layer has weak charge density wave (CDW) pattern and reduces the CDW coupling between the adjacent 1T-TaS$_2$ layers. In the 1T-TaS$_2$ layer of 4Hb-TaS$_2$, we observe a narrow electronic band located near Fermi level, and its spatial distribution is consistent with the tight-binding calculations for two-dimensional 1T-TaS$_2$ layers. The weak electronic hybridization between the 1T-TaS$_2$ and 1H-TaS$_2$ layers in 4Hb-TaS$_2$ shifts the narrow electronic band to be slightly above the Fermi level, which suppresses the electronic correlation induced band splitting. In contrast, in bulk 1T-TaS$_2$, there is an interlayer CDW coupling induced insulating gap. In comparison with the spatial distributions of the electronic states in bulk 1T-TaS$_2$ and 4Hb-TaS$_2$, the insulating gap in bulk 1T-TaS$_2$ results from the formation of a bonding band and an antibonding band due to the overlap of the narrow electronic bands in the dimerized 1T-TaS$_2$ layers.

cond-mat.mes-hall↗