Tootfinder

Asymmetric Effects Underlying Dynamic Heterogeneity in Miscible Blends of Poly(methyl methacrylate) with Poly(ethylene oxide)
Shannon Zhang, Michael A. Webb
https://arxiv.org/abs/2506.12143

Asymmetric Effects Underlying Dynamic Heterogeneity in Miscible Blends of Poly(methyl methacrylate) with Poly(ethylene oxide)
The emergence of spatially variable local dynamics, or dynamic heterogeneity, is common in multicomponent polymer systems. Such heterogeneity is understood to arise from differences between the intrinsic dynamical fluctuations associated with one component versus another. However, the nature of the dynamic coupling between these components and how it depends on composition, temperature, and environmental fluctuations is not fully understood. Here, we use molecular dynamics simulations to charac…

US unveils 'reliable and cost-effective' drone to rival Iranian-designed Shaheds: https://benborges.xyz/2025/07/17/us-unveils-reliable-and-costeffective.html

🇺🇦 #NowPlaying on KEXP's #DriveTime
Des Demonas:
🎵 The Duke Ellington Bridge
#DesDemonas
https://des-demonas.bandcamp.com/track/the-duke-elington-bridge
https://open.spotify.com/track/5E1F4ZhdWKkIrPcEGLVYF7

Binary choice logit models with general fixed effects for panel and network data
Kevin Dano, Bo E. Honor\'e, Martin Weidner
https://arxiv.org/abs/2508.11556 https://

Binary choice logit models with general fixed effects for panel and network data
This paper systematically analyzes and reviews identification strategies for binary choice logit models with fixed effects in panel and network data settings. We examine both static and dynamic models with general fixed-effect structures, including individual effects, time trends, and two-way or dyadic effects. A key challenge is the incidental parameter problem, which arises from the increasing number of fixed effects as the sample size grows. We explore two main strategies for eliminating nui…

Understanding the Effect of Knowledge Graph Extraction Error on Downstream Graph Analyses: A Case Study on Affiliation Graphs
Erica Cai, Brendan O'Connor
https://arxiv.org/abs/2506.12367

Understanding the Effect of Knowledge Graph Extraction Error on Downstream Graph Analyses: A Case Study on Affiliation Graphs
Knowledge graphs (KGs) are useful for analyzing social structures, community dynamics, institutional memberships, and other complex relationships across domains from sociology to public health. While recent advances in large language models (LLMs) have improved the scalability and accessibility of automated KG extraction from large text corpora, the impacts of extraction errors on downstream analyses are poorly understood, especially for applied scientists who depend on accurate KGs for real-wo…

Comment on "Properties and dynamics of generalized squeezed states"
Rub\'en Gordillo, Ricardo Puebla
https://arxiv.org/abs/2507.12250 https:/…

Comment on "Properties and dynamics of generalized squeezed states"
A recent article [S. Ashhab and M. Ayyash, New J. Phys. 27, 054104 (2025)] has reported unexpected oscillatory dynamics in generalized squeezed states of order higher than two as their squeezing parameter increases. This behaviour, observed through numerical simulations using truncated bosonic annihilation and creation operators, appeared in several properties of these states, including their average photon number. The authors argued that these oscillations reflect a genuine physical effect. He…

SINDybrid: automatic generation of hybrid models for dynamic systems
Ulderico Di Caprio, M. Enis Leblebici
https://arxiv.org/abs/2506.12498 https://…

SINDybrid: automatic generation of hybrid models for dynamic systems
Hybrid modelling enhances the accuracy and predictive capability of dynamic models by integrating first principles with data-driven methods, effectively mitigating epistemic uncertainties inherent in mechanistic approaches. However, hybrid model construction remains complex, typically requiring expert knowledge to identify model epistemic uncertainty and select suitable machine-learning components to capture it. This complexity limits broader adoption in research and industry. We introduce SIND…

Defect Interactions Through Periodic Boundaries in Two-Dimensional $p$-atics
Cody D. Schimming
https://arxiv.org/abs/2507.12597 https://

Defect Interactions Through Periodic Boundaries in Two-Dimensional $p$-atics
Periodic boundary conditions are a common tool used to emulate effectively infinite domains. However, two-dimensional periodic domains are topologically distinct from the infinite plane, eliciting the question: How do periodic boundaries affect systems with topological properties themselves? In this work, I derive an analytical expression for the orientation fields of two-dimensional $p$-atic liquid crystals, systems with $p$-fold rotational symmetry, with topological defects in a flat domain s…

Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
Chong Li, Yingzhuo Deng, Jiajun Zhang, Chengqing Zong
https://arxiv.org/abs/2506.12388

Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
The curse of multilinguality phenomenon is a fundamental problem of multilingual Large Language Models (LLMs), where the competition between massive languages results in inferior performance. It mainly comes from limited capacity and negative transfer between dissimilar languages. To address this issue, we propose a method to dynamically group and scale up the parameters of multilingual LLM while boosting positive transfer among similar languages. Specifically, the model is first tuned on monol…

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
Arjun R. Akula, Kazuma Hashimoto, Krishna Srinivasan, Aditi Chaudhary, Karthik Raman, Michael Bendersky
https://arxiv.org/abs/2506.12346

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
The emergence of long-context large language models (LLMs) has enabled the use of hundreds, or even thousands, of demonstrations for in-context learning (ICL) - a previously impractical regime. This paper investigates whether traditional ICL selection strategies, which balance the similarity of ICL examples to the test input (using a text retriever) with diversity within the ICL set, remain effective when utilizing a large number of demonstrations. Our experiments demonstrate that, while longer…