Tootfinder

Structural Equation Modeling with Latent Variables and Composites
Tamara Schamberger, Florian Schuberth, J\"org Henseler, Yves Rosseel
https://arxiv.org/abs/2508.06112 http…

Structural Equation Modeling with Latent Variables and Composites
Structural equation modeling (SEM) is a prevalent approach for studying constructs. Traditionally, these constructs are modeled as reflectively measured latent variables - common factors that account for the variance-covariance structure of their associated indicators. Over the past two decades, there has been growing interest in an alternative way of modeling constructs: the composite, i.e., a linear combination of indicators. However, existing approaches to estimating composite models either …

Chirality in Action: Time-Aware Video Representation Learning by Latent Straightening
Piyush Bagad, Andrew Zisserman
https://arxiv.org/abs/2509.08502 https://

Chirality in Action: Time-Aware Video Representation Learning by Latent Straightening
Our objective is to develop compact video representations that are sensitive to visual change over time. To measure such time-sensitivity, we introduce a new task: chiral action recognition, where one needs to distinguish between a pair of temporally opposite actions, such as "opening vs. closing a door", "approaching vs. moving away from something", "folding vs. unfolding paper", etc. Such actions (i) occur frequently in everyday life, (ii) require understanding of simple visual change over ti…

Thermochemical models of outer core convection with heterogeneous core-mantle boundary heat flux
Souvik Naskar, Jonathan E. Mound, Christopher J. Davies, Andrew T. Clarke
https://arxiv.org/abs/2507.03538

Thermochemical models of outer core convection with heterogeneous core-mantle boundary heat flux
Thermochemical convection in Earth's outer core is driven by the crystallisation of the inner core that releases latent heat and light elements. A key question in core dynamics is whether a stable layer exists just below the core-mantle boundary. Recent core convection simulations, accounting for CMB heterogeneities, propose locally stable regions (or regional inversion lenses, RILs) rather than a global layer, allowing both stable and unstable regions to coexist. In this study, we consider a s…

ConfLogger: Enhance Systems' Configuration Diagnosability through Configuration Logging
Shiwen Shan, Yintong Huo, Yuxin Su, Zhining Wang, Dan Li, Zibin Zheng
https://arxiv.org/abs/2508.20977

ConfLogger: Enhance Systems' Configuration Diagnosability through Configuration Logging
Modern configurable systems offer customization via intricate configuration spaces, yet such flexibility introduces pervasive configuration-related issues such as misconfigurations and latent softwarebugs. Existing diagnosability supports focus on post-failure analysis of software behavior to identify configuration issues, but none of these approaches look into whether the software clue sufficient failure information for diagnosis. To fill in the blank, we propose the idea of configuration logg…

Vecchia approximated Bayesian heteroskedastic Gaussian processes
Parul V. Patil, Robert B. Gramacy, Cayelan C. Carey, R. Quinn Thomas
https://arxiv.org/abs/2507.07815

Vecchia approximated Bayesian heteroskedastic Gaussian processes
Many computer simulations are stochastic and exhibit input dependent noise. In such situations, heteroskedastic Gaussian processes (hetGPs) make ideal surrogates as they estimate a latent, non-constant variance. However, existing hetGP implementations are unable to deal with large simulation campaigns and use point-estimates for all unknown quantities, including latent variances. This limits applicability to small experiments and undercuts uncertainty. We propose a Bayesian hetGP using elliptic…

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Yingji Zhang, Danilo S. Carvalho, Andr\'e Freitas
https://arxiv.org/abs/2506.20083

Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder
Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, compositionality, and generalisation capabilities of Transformer-based auto-regressive language models (LMs). In this survey, we offer a novel perspective on latent space geometry through the lens of compositional semantics, a direction we refer to as \textit{semantic representation learning}. This direction enables a bridge between symbolic and distri…

When do World Models Successfully Learn Dynamical Systems?
Edmund Ross, Claudia Drygala, Leonhard Schwarz, Samir Kaiser, Francesca di Mare, Tobias Breiten, Hanno Gottschalk
https://arxiv.org/abs/2507.04898

When do World Models Successfully Learn Dynamical Systems?
In this work, we explore the use of compact latent representations with learned time dynamics ('World Models') to simulate physical systems. Drawing on concepts from control theory, we propose a theoretical framework that explains why projecting time slices into a low-dimensional space and then concatenating to form a history ('Tokenization') is so effective at learning physics datasets, and characterise when exactly the underlying dynamics admit a reconstruction mapping from the history of pre…

Estimating Vertical Velocity in Convective Updrafts from Temperature, Pressure, and Latent Heating
Amel Derras-Chouk, Gregory Elsaesser, Zhengzhao Johnny Luo, Toshi Matsui, Andreas F. Prein, Jingbo Wu
https://arxiv.org/abs/2508.16750

Estimating Vertical Velocity in Convective Updrafts from Temperature, Pressure, and Latent Heating
The vertical velocity in convective clouds ($w_c$) mediates convective anvil development and global moisture transport, influencing Earth's energy budget, but has yet to be estimated globally over long periods due to the absence of spaceborne retrievals. Here, a method for estimating $w_c$ given vertical profiles of in-cloud temperature, pressure, and latent heating rate is presented and assessed. The method relies on analytical models for the approximately linear relationship between $w_c$ and…

From One to More: Contextual Part Latents for 3D Generation
Shaocong Dong, Lihe Ding, Xiao Chen, Yaokun Li, Yuxin Wang, Yucheng Wang, Qi Wang, Jaehyeok Kim, Chenjian Gao, Zhanpeng Huang, Zibin Wang, Tianfan Xue, Dan Xu
https://arxiv.org/abs/2507.08772

From One to More: Contextual Part Latents for 3D Generation
Recent advances in 3D generation have transitioned from multi-view 2D rendering approaches to 3D-native latent diffusion frameworks that exploit geometric priors in ground truth data. Despite progress, three key limitations persist: (1) Single-latent representations fail to capture complex multi-part geometries, causing detail degradation; (2) Holistic latent coding neglects part independence and interrelationships critical for compositional design; (3) Global conditioning mechanisms lack fine-…

Misspecifications in structural equation modeling: The choice of latent variables, causal-formative constructs or composites
Jonas Bauer, Axel Mayer, Christiane Fuchs, Tamara Schamberger
https://arxiv.org/abs/2507.21998

Misspecifications in structural equation modeling: The choice of latent variables, causal-formative constructs or composites
Empirical research in many social disciplines involves constructs that are not directly observable, such as behaviors. To model them, constructs must be operationalized using their relations with indicators. Structural equation modeling (SEM) is the primary approach for this purpose. In SEM, three types of constructs are distinguished: latent variables, causal-formative constructs, and composites. To estimate the parameters of the different models, various estimators have been developed. Many M…