Tootfinder

from my link log —
Tour of a Scheme pattern matcher: expression and pattern expansion.
https://crumbles.blog/posts/2025-11-09-extensible-match-front-end.html
saved 2025-11-14

Na stronie CBA podstrona „Kontrole” jest wciąż w budowie, ale mają już podstronę o Archaniele Gabrielu
https://www.cba.gov.pl/pl/o-nas/patron-archaniol-gabriel/5031,Patron-Archaniol-Gabriel.html

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
Jingyu Tang, Chaoran Chen, Jiawen Li, Zhiping Zhang, Bingcan Guo, Ibrahim Khalilov, Simret Araya Gebreegziabher, Bingsheng Yao, Dakuo Wang, Yanfang Ye, Tianshi Li, Ziang Xiao, Yaxing Yao, Toby Jia-Jun Li
https://arxiv.org/abs/…

Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight
The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks from high-level intents, understanding how dark patterns affect agents is increasingly important. We present a two-phase empirical study examining how agents, human participants, and human-AI teams respond to 16 types of dark patterns across diverse scenario…

One of the interesting articles that came after #KubeCon is touching the problem of the platform engineering anti-patterns. Is there anything in particular that bothers you and you want to discuss it at #DevOpsDays #Prague

8 platform engineering anti-patterns
Golden paths gone gray? Avoid these common mistakes that sink platform engineering initiatives.

Quantifying topological features and irregularities in zebrafish patterns using the sweeping-plane filtration
Nour Khoudari, John Nardini, Alexandria Volkening
https://arxiv.org/abs/2509.11023

Quantifying topological features and irregularities in zebrafish patterns using the sweeping-plane filtration
Complex patterns emerge across a wide range of biological systems. While such patterns often exhibit remarkable robustness, variation and irregularity exist at multiple scales and can carry important information about the underlying agent interactions driving collective dynamics. Many methods for quantifying biological patterns focus on large-scale, characteristic features (such as stripe width or spot number), but questions remain on how to characterize messy patterns. In the case of cellular …

High-capacity associative memory in a quantum-optical spin glass
Brendan P. Marsh, David Atri Schuller, Yunpeng Ji, Henry S. Hunt, Surya Ganguli, Sarang Gopalakrishnan, Jonathan Keeling, Benjamin L. Lev
https://arxiv.org/abs/2509.12202

High-capacity associative memory in a quantum-optical spin glass
The Hopfield model describes a neural network that stores memories using all-to-all-coupled spins. Memory patterns are recalled under equilibrium dynamics. Storing too many patterns breaks the associative recall process because frustration causes an exponential number of spurious patterns to arise as the network becomes a spin glass. Despite this, memory recall in a spin glass can be restored, and even enhanced, under quantum-optical nonequilibrium dynamics because spurious patterns can now ser…

Topological Signatures of ReLU Neural Network Activation Patterns
Vicente Bosca, Tatum Rask, Sunia Tanweer, Andrew R. Tawfeek, Branden Stone
https://arxiv.org/abs/2510.12700 htt…

Topological Signatures of ReLU Neural Network Activation Patterns
This paper explores the topological signatures of ReLU neural network activation patterns. We consider feedforward neural networks with ReLU activation functions and analyze the polytope decomposition of the feature space induced by the network. Mainly, we investigate how the Fiedler partition of the dual graph and show that it appears to correlate with the decision boundary -- in the case of binary classification. Additionally, we compute the homology of the cellular decomposition -- in a regr…

A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
Sepideh Masoudi, Mark Edward Michael Daly, Jannis Kiesel, Stefan Tai
https://arxiv.org/abs/2510.12354

A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
As data mesh architectures gain traction in federated environments, organizations are increasingly building consumer-specific data-sharing pipelines using modular, cloud-native transformation services. Prior work has shown that structuring these pipelines with reusable transformation stages enhances both scalability and energy efficiency. However, integrating traditional cloud design patterns into such pipelines poses a challenge: predefining and embedding patterns can compromise modularity, re…

Human-AI Use Patterns for Decision-Making in Disaster Scenarios: A Systematic Review
Emmanuel Adjei Domfeh, Christopher L. Dancy
https://arxiv.org/abs/2509.12034 https://…

Human-AI Use Patterns for Decision-Making in Disaster Scenarios: A Systematic Review
In high-stakes disaster scenarios, timely and informed decision-making is critical yet often challenged by uncertainty, dynamic environments, and limited resources. This paper presents a systematic review of Human-AI collaboration patterns that support decision-making across all disaster management phases. Drawing from 51 peer-reviewed studies, we identify four major categories: Human-AI Decision Support Systems, Task and Resource Coordination, Trust and Transparency, and Simulation and Trainin…

The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models
Yike Shi (Diane), Qing Xiao (Diane), Qing (Diane), Hu, Hong Shen, Hua Shen
https://arxiv.org/abs/2509.10830

The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models
Large language models can influence users through conversation, creating new forms of dark patterns that differ from traditional UX dark patterns. We define LLM dark patterns as manipulative or deceptive behaviors enacted in dialogue. Drawing on prior work and AI incident reports, we outline a diverse set of categories with real-world examples. Using them, we conducted a scenario-based study where participants (N=34) compared manipulative and neutral LLM responses. Our results reveal that recog…