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Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans

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arXiv 2024年

作者： Lee, Messi H.J. Montgomery, Jacob M. Lai, Calvin K. Division of Computational and Data Sciences Washington University St. Louis United States Department of Political Science Washington University St. Louis United States Department of Psychological & Brain Sciences Washington University St. Louis United States

Large language models (LLMs) are becoming pervasive in everyday life, yet their propensity to reproduce biases inherited from training data remains a pressing concern. Prior investigations into bias in LLMs have focused on the association of social groups with stereotypical attributes. However, this is only one form of human bias such systems may reproduce. We investigate a new form of bias in LLMs that resembles a social psychological phenomenon where socially subordinate groups are perceived as more homogeneous than socially dominant groups. We had ChatGPT, a state-of-the-art LLM, generate texts about intersectional group identities and compared those texts on measures of homogeneity. We consistently found that ChatGPT portrayed African, Asian, and Hispanic Americans as more homogeneous than White Americans, indicating that the model described racial minority groups with a narrower range of human experience. ChatGPT also portrayed women as more homogeneous than men, but these differences were small. Finally, we found that the effect of gender differed across racial/ethnic groups such that the effect of gender was consistent within African and Hispanic Americans but not within Asian and White Americans. We argue that the tendency of LLMs to describe groups as less diverse risks perpetuating stereotypes and discriminatory behavior. © 2024, CC BY-NC-ND.

关键词： computational linguistics

Deep Phenotyping of Non-Alcoholic Fatty Liver Disease Patients with Genetic Factors for Insights into the Complex Disease

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arXiv 2023年

作者： Priya, Tahmina Sultana Leng, Fan Luehrs, Anthony C. Klee, Eric W. Allen, Alina M. Lazaridis, Konstantinos N. Yao, Danfeng Daphne Tian, Shulan Department of Computer Science Virginia Tech VA United States Data Analytics and Integration Mayo Clinic Rochester United States Division of Computational Biology Mayo Clinic Rochester United States Division of Gastroenterology and Hepatology Mayo Clinic Rochester United States

Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disorder characterized by the excessive accumulation of fat in the liver in individuals who do not consume significant amounts of alcohol, including risk factors like obesity, insulin resistance, type 2 diabetes, etc. We aim to identify subgroups of NAFLD patients based on demographic, clinical, and genetic characteristics for precision medicine. The genomic and phenotypic data (3,408 cases and 4,739 controls) for this study were gathered from participants in Mayo Clinic Tapestry Study (IRB#19-000001) and their electric health records, including their demographic, clinical, and comorbidity data, and the genotype information through whole ex-ome sequencing performed at Helix using the Exome+® Assay according to standard procedure (***). Factors highly relevant to NAFLD were determined by the chi-square test and stepwise backward-forward regression model. Latent class analysis (LCA) was performed on NAFLD cases using significant indicator variables to identify subgroups. Copyright © 2023, The Authors. All rights reserved.

关键词： Diseases

L2-OPTIMAL REDUCED-ORDER MODELING USING PARAMETER-SEPARABLE FORMS

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arXiv 2022年

作者： Mlinarić, Petar Gugercin, Serkan Department of Mathematics Virginia Tech BlacksburgVA24061 United States Division of Computational Modeling and Data Analytics Academy of Data Science Virginia Tech BlacksburgVA24061 United States

We provide a unifying framework for L2-optimal reduced-order modeling for linear time-invariant dynamical systems and stationary parametric problems. Using parameter-separable forms of the reduced-model quantities, we derive the gradients of the L2 cost function with respect to the reduced matrices, which then allows a non-intrusive, data-driven, gradient-based descent algorithm to construct the optimal approximant using only output samples. By choosing an appropriate measure, the framework covers both continuous (Lebesgue) and discrete cost functions. We show the efficacy of the proposed algorithm via various numerical examples. Furthermore, we analyze under what conditions the data-driven approximant can be obtained via projection. Copyright © 2022, The Authors. All rights reserved.

关键词： Optimization

Noninvertibility and non-Markovianity of quantum dynamical maps

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Physical Review A 2023年第4期108卷 042202-042202页

作者： Vinayak Jagadish R. Srikanth Francesco Petruccione Instytut Fizyki Teoretycznej Uniwersytet Jagielloński Łojasiewicza 11 30-348 Kraków Poland Theoretical Sciences Division Poornaprajna Institute of Scientific Research (PPISR) Bidalur Post Devanahalli Bengaluru 562164 India School for Data Science and Computational Thinking Stellenbosch University Stellenbosch 7600 South Africa National Institute for Theoretical and Computational Sciences (NITheCS) Stellenbosch 7600 South Africa

We identify two broad types of noninvertibilities in quantum dynamical maps, one necessarily associated with CP indivisibility and one not so. We study the production of (non-)Markovian, invertible maps by the process of mixing noninvertible Pauli maps and quantify the fraction of the same. The memory kernel perspective appears to be less transparent on the issue of invertibility than the approaches based on maps or master equations. Here we consider a related and potentially helpful issue: the identification of criteria of parameterized families of maps leading to the existence of a well-defined semigroup limit.

关键词： Open quantum systems & decoherence

Active Geospatial Search for Efficient Tenant Eviction Outreach 39

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Active Geospatial Search for Efficient Tenant Eviction Outre...

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Sarkar, Anindya DiChristofano, Alex Das, Sanmay Fowler, Patrick J. Jacobs, Nathan Vorobeychik, Yevgeniy Department of Computer Science and Engineering Washington University St. Louis United States Department of Computer Science and Engineering George Mason University United States Division of Computational & Data Sciences Washington University St. Louis United States Brown School at Washington University St. Louis United States

ISBN: (纸本)157735897X

Tenant evictions threaten housing stability and are a major concern for many cities. An open question concerns whether data-driven methods enhance outreach programs that target at-risk tenants to mitigate their risk of eviction. We propose a novel active geospatial search (AGS) modeling framework for this problem. AGS integrates property-level information in a search policy that identifies a sequence of rental units to canvas to both determine their eviction risk and provide support if needed. We propose a hierarchical reinforcement learning approach to learn a search policy for AGS that scales to large urban areas containing thousands of parcels, balancing exploration and exploitation and accounting for travel costs and a budget constraint. Crucially, the search policy adapts online to newly discovered information about evictions. Evaluation using eviction data for a large urban area demonstrates that the proposed framework and algorithmic approach are considerably more effective at sequentially identifying eviction cases than baseline methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Reinforcement learning

Structural phase transitions between layered Indium Selenide for integrated photonic memory

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arXiv 2025年

作者： Li, Tiantian Wang, Yong Li, Wei Mao, Dun Benmore, Chris J. Evangelista, Igor Xing, Huadan Li, Qiu Wang, Feifan Sivaraman, Ganesh Janotti, Anderson Law, Stephanie Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Materials Science and Engineering University of Delaware NewarkDE19716 United States Los Alamos National Laboratory Computer Computational and Statistical Sciences Division Los AlamosNM87545 United States X-ray Science Division Argonne National Laboratory LemontIL60439 United States Data Science and Learning Division Argonne National Laboratory LemontIL60439 United States

The primary mechanism of optical memoristive devices relies on the phase transitions between amorphous-crystalline states. The slow or energy hungry amorphous-crystalline transitions in optical phase-change materials are detrimental to the devices’ scalability and performance. Leveraging the integrated photonic platform, we demonstrate a single nanosecond pulse triggered nonvolatile and reversible switching between two layered structures of indium selenide (In2Se3). High resolution pair distribution function reveals the detailed atomistic transition pathways between the layered structures. With inter-layer ‘shear glide’ and isosymmetric phase transition, the switching between α- and β-structural states contain low re-configurational entropy, allowing reversible switching between layered structures. Broadband refractive index contrast, optical transparency, and volumetric effect in the crystalline-crystalline phase transition are experimentally characterized in molecular beam epitaxy-grown thin films and compared to ab-initial calculations. The nonlinear resonator transmission spectra measure incremental linear loss rate of 3.3 GHz introduced by 1.5 µm long In2Se3 covered layer, resulting from the combinations of material absorption and scattering. © 2025, CC BY.

关键词： Molecular beam epitaxy

Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions with Applications

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arXiv 2024年

作者： Iguchi, Yuga Jasra, Ajay Maama, Mohamed Beskos, Alexandros Department of Statistical Science University College London LondonWC1E 6BT United Kingdom School of Data Science The Chinese University of Hong Kong Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we present a new antithetic multilevel Monte Carlo (MLMC) method for the estimation of expectations with respect to laws of diffusion processes that can be elliptic or hypo-elliptic. In particular, we consider the case where one has to resort to time discretization of the diffusion and numerical simulation of such schemes. Motivated by recent developments, we introduce a new MLMC estimator of expectations, which does not require simulation of intractable Lévy areas but has a weak error of order 2 and achieves the optimal computational complexity. We then show how this approach can be used in the context of the filtering problem associated to partially observed diffusions with discrete time observations. We illustrate with numerical simulations that our new approaches provide efficiency gains for several problems relative to some existing methods. © 2024, CC BY.

关键词： Diffusion

A UNIFYING FRAMEWORK FOR INTERPOLATORY L2-OPTIMAL REDUCED-ORDER MODELING

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arXiv 2022年

作者： Mlinarić, Petar Gugercin, Serkan Department of Mathematics Virginia Tech BlacksburgVA24061 United States Department of Mathematics Division of Computational Modeling and Data Analytics Academy of Data Science Virginia Tech BlacksburgVA24061 United States

We develop a unifying framework for interpolatory L2-optimal reduced-order modeling for a wide classes of problems ranging from stationary models to parametric dynamical systems. We first show that the framework naturally covers the well-known interpolatory necessary conditions for H2-optimal model order reduction and leads to the interpolatory conditions for H2 ⨂ L2-optimal model order reduction of multi-input/multi-output parametric dynamical systems. Moreover, we derive novel interpolatory optimality conditions for rational discrete least-squares minimization and for L2-optimal model order reduction of a class of parametric stationary models. We show that bitangential Hermite interpolation appears as the main tool for optimality across different domains. The theoretical results are illustrated on two numerical examples. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear time-invariant system

"It Is Hard to Remove from My Eye": Design Makeup Residue Visualization System for Chinese Traditional Opera (Xiqu) Performers

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arXiv 2024年

作者： Xiong, Zeyu Fu, Shihan Zhu, Yanying Zhu, Chenqing Ma, Xiaojuan Fan, Mingming Computational Media and Arts Thrust The Hong Kong University of Science and Technology Guangzhou China Data Science and Analysis Thrust The Hong Kong University of Science and Technology Guangzhou China Internet of Things Thrust The Hong Kong University of Science and Technology Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

Chinese traditional opera (Xiqu) performers often experience skin problems due to the long-term use of heavy-metal-laden face paints. To explore the current skincare challenges encountered by Xiqu performers, we conducted an online survey (N=136) and semi-structured interviews (N=15) as a formative study. We found that incomplete makeup removal is the leading cause of human-induced skin problems, especially the difficulty in removing eye makeup. Therefore, we proposed EyeVis, a prototype that can visualize the residual eye makeup and record the time make-up was worn by Xiqu performers. We conducted a 7-day deployment study (N=12) to evaluate EyeVis. Results indicate that EyeVis helps to increase Xiqu performers' awareness about removing makeup, as well as boosting their confidence and security in skincare. Overall, this work also provides implications for studying the work of people who wear makeup on a daily basis, and helps to promote and preserve the intangible cultural heritage of practitioners. © 2024, CC BY-NC-ND.

关键词： Computer vision