Tootfinder

A systematic comparison of Large Language Models for automated assignment assessment in programming education: Exploring the importance of architecture and vendor
Marcin Jukiewicz
https://arxiv.org/abs/2509.26483

A systematic comparison of Large Language Models for automated assignment assessment in programming education: Exploring the importance of architecture and vendor
This study presents the first large-scale, side-by-side comparison of contemporary Large Language Models (LLMs) in the automated grading of programming assignments. Drawing on over 6,000 student submissions collected across four years of an introductory programming course, we systematically analysed the distribution of grades, differences in mean scores and variability reflecting stricter or more lenient grading, and the consistency and clustering of grading patterns across models. Eighteen pub…

Visual Analytics for Causal Reasoning from Real-World Health Data
Arran Zeyu Wang, David Borland, David Gotz
https://arxiv.org/abs/2508.17474 https://arxiv…

Visual Analytics for Causal Reasoning from Real-World Health Data
The increasing capture and analysis of large-scale longitudinal health data offer opportunities to improve healthcare and advance medical understanding. However, a critical gap exists between (a) -- the observation of patterns and correlations, versus (b) -- the understanding of true causal mechanisms that drive outcomes. An accurate understanding of the underlying mechanisms that cause various changes in medical status is crucial for decision-makers across various healthcare domains and roles,…

An Anthropic report details how Claude usage varies by country and US states, finding 36% use it for coding, 77% of enterprise use is for automation, and more (Anthropic)
https://www.anthropic.com/research/anthropic-economic-index-september-2025-report

Anthropic Economic Index report: Uneven geographic and enterprise AI adoption
To study such patterns of early AI adoption, we extend the Anthropic Economic Index along two important dimensions, introducing a geographic analysis of Claude.ai conversations and a first-of-its-kind examination of enterprise API use. We show how Claude usage has evolved over time, how adoption patterns differ across regions, and—for the first time—how firms are deploying frontier AI to solve business problems.

Learning Short-Term and Long-Term Patterns of High-Order Dynamics in Real-World Networks
Yunyong Ko, Da Eun Lee, Song Kyung Yu, Sang-Wook Kim
https://arxiv.org/abs/2508.17236 ht…

Learning Short-Term and Long-Term Patterns of High-Order Dynamics in Real-World Networks
Real-world networks have high-order relationships among objects and they evolve over time. To capture such dynamics, many works have been studied in a range of fields. Via an in-depth preliminary analysis, we observe two important characteristics of high-order dynamics in real-world networks: high-order relations tend to (O1) have a structural and temporal influence on other relations in a short term and (O2) periodically re-appear in a long term. In this paper, we propose LINCOLN, a method for…

ExtGraph: A Fast Extraction Method of User-intended Graphs from a Relational Database
Jeongho Park, Geonho Lee, Min-Soo Kim
https://arxiv.org/abs/2509.18534 https://

Patterns in the Transition From Founder-Leadership to Community Governance of Open Source
Mobina Noori, Mahasweta Chakraborti, Amy X Zhang, Seth Frey
https://arxiv.org/abs/2509.16295

Patterns in the Transition From Founder-Leadership to Community Governance of Open Source
Open digital public infrastructure needs community management to ensure accountability, sustainability, and robustness. Yet open-source projects often rely on centralized decision-making, and the determinants of successful community management remain unclear. We analyze 637 GitHub repositories to trace transitions from founder-led to shared governance. Specifically, we document trajectories to community governance by extracting institutional roles, actions, and deontic cues from version-control…

Finally, what Xia & Lindell call a "separation problem" is, in our view, a feature of our approach and not a bug.
If, e.g., all languages in a family are polysynthetic (or none are), that’s not a statistical artefact – it’s the signal. The outcome is well associated with genealogy, showing that family membership captures someth genuinely informative about the process. When the model finds that family explains a large share of the variance, that's not a failure–it's evidence that phylogenetic structure dominates the pattern.
So while Xia & Lindell insist that "autocorrelation due to relationships and distance cannot be captured in family or regional-level analyses", we see that as an empirical question – and we treated it as one.
The real test is whether a mixed model that explicitly represents phylogeny and geography performs worse than their alternative, where the entire shared history of languages and environments is effectively collapsed into a single dimension (an eigenvector).
In other words: we model relationships – Xia & Lindell summarise them into one number per language.

Mutual Information Tracks Policy Coherence in Reinforcement Learning
Cameron Reid, Wael Hafez, Amirhossein Nazeri
https://arxiv.org/abs/2509.10423 https://…

Mutual Information Tracks Policy Coherence in Reinforcement Learning
Reinforcement Learning (RL) agents deployed in real-world environments face degradation from sensor faults, actuator wear, and environmental shifts, yet lack intrinsic mechanisms to detect and diagnose these failures. We present an information-theoretic framework that reveals both the fundamental dynamics of RL and provides practical methods for diagnosing deployment-time anomalies. Through analysis of state-action mutual information patterns in a robotic control task, we first demonstrate that…

Planet Earth in reflected and polarized light -- III. Modeling and analysis of a decade-long catalog of Earthshine observations
Giulia Roccetti, Michael F. Sterzik, Claudia Emde, Mihail Manev, Stefano Bagnulo, Julia V. Seidel
https://arxiv.org/abs/2509.13415

Planet Earth in reflected and polarized light - III. Modeling and analysis of a decade-long catalog of Earthshine observations
Earthshine observations offer a unique opportunity to study Earth as an exoplanet seen from the Moon. As the Sun-Earth-Moon geometry changes, Earth can be observed as a spatially unresolved exoplanet at different phase angles, providing important context for future observations of Earth-like exoplanets. Here, we present a catalog of Earthshine polarization spectra obtained with FORS2 on the VLT, covering diverse scenes, surface conditions, cloud properties, and weather patterns for over a decad…

"My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community
Pat Pataranutaporn, Sheer Karny, Chayapatr Archiwaranguprok, Constanze Albrecht, Auren R. Liu, Pattie Maes
https://arxiv.org/abs/2509.11391

"My Boyfriend is AI": A Computational Analysis of Human-AI Companionship in Reddit's AI Community
Human-AI interaction researchers face an overwhelming challenge: synthesizing insights from thousands of empirical studies to understand how AI impacts people and inform effective design. Existing approach for literature reviews cluster papers by similarities, keywords or citations, missing the crucial cause-and-effect relationships that reveal how design decisions impact user outcomes. We introduce the Atlas of Human-AI Interaction, an interactive web interface that provides the first systemat…