Tootfinder

Why Academics Are Leaving Twitter for Bluesky
Dorian Quelle, Frederic Denker, Prashant Garg, Alexandre Bovet
https://arxiv.org/abs/2505.24801 https://

Why Academics Are Leaving Twitter for Bluesky
We analyse the migration of 300,000 academic users from Twitter/X to Bluesky between 2023 and early 2025, combining rich bibliometric data, longitudinal social-media activity, and a novel cross-platform identity-matching pipeline. We show that 18% of scholars in our sample transitioned, with transition rates varying sharply by discipline, political expression, and Twitter engagement but not by traditional academic metrics. Using time-varying Cox models and a matched-pairs design, we isolate gen…

Automated Feedback on Student-Generated UML and ER Diagrams Using Large Language Models
Sebastian G\"urtl, Gloria Schimetta, David Kerschbaumer, Michael Liut, Alexander Steinmaurer
https://arxiv.org/abs/2507.23470

Automated Feedback on Student-Generated UML and ER Diagrams Using Large Language Models
UML and ER diagrams are foundational in computer science education but come with challenges for learners due to the need for abstract thinking, contextual understanding, and mastery of both syntax and semantics. These complexities are difficult to address through traditional teaching methods, which often struggle to provide scalable, personalized feedback, especially in large classes. We introduce DUET (Diagrammatic UML & ER Tutor), a prototype of an LLM-based tool, which converts a reference d…

Deep learning-based segmentation of T1 and T2 cardiac MRI maps for automated disease detection
Andreea Bianca Popescu, Andreas Seitz, Heiko Mahrholdt, Jens Wetzl, Athira Jacob, Lucian Mihai Itu, Constantin Suciu, Teodora Chitiboi
https://arxiv.org/abs/2507.00903

Deep learning-based segmentation of T1 and T2 cardiac MRI maps for automated disease detection
Objectives Parametric tissue mapping enables quantitative cardiac tissue characterization but is limited by inter-observer variability during manual delineation. Traditional approaches relying on average relaxation values and single cutoffs may oversimplify myocardial complexity. This study evaluates whether deep learning (DL) can achieve segmentation accuracy comparable to inter-observer variability, explores the utility of statistical features beyond mean T1/T2 values, and assesses whether ma…

Fermion parity and quantum capacitance oscillation with partially separated Majorana and quasi-Majorana modes
Tudor D. Stanescu, Sumanta Tewari
https://arxiv.org/abs/2505.23741

Fermion parity and quantum capacitance oscillation with partially separated Majorana and quasi-Majorana modes
In a recent experiment, flux dependent oscillations of the quantum capacitance were observed in a one dimensional spin-orbit coupled semiconductor superconductor heterostructure connected end to end via a quantum dot and threaded by a magnetic flux. In the topological superconducting phase of the heterostructure, the oscillations corresponding to different fermion parity sectors are shifted by half a period and can serve as a mechanism for fermion parity readout or fusion operations involving a…

Covariant phase space and $L_\infty$ algebras
Vin\'icius Bernardes, Theodore Erler, Atakan Hilmi F{\i}rat
https://arxiv.org/abs/2506.20706 https://

Covariant phase space and $L_\infty$ algebras
We propose a symplectic structure for the phase space of a generic Lagrangian field theory expressed in the framework of $L_\infty$ algebras. The symplectic structure does not require explicit knowledge of the derivative content of the Lagrangian, and therefore is applicable to nonlocal models, such as string field theory, where traditional constructions are difficult to apply. We test our proposal in a number of examples ranging from general relativity to $p$-adic string theory.

The Stablecoin Discount: Evidence of Tether's U.S. Treasury Bill Market Share in Lowering Yields
Lennart Ante, Aman Saggu, Ingo Fiedler
https://arxiv.org/abs/2505.12413

The Stablecoin Discount: Evidence of Tether's U.S. Treasury Bill Market Share in Lowering Yields
Stablecoins represent a critical bridge between cryptocurrency and traditional finance, with Tether (USDT) dominating the sector as the largest stablecoin by market capitalization. By Q1 2025, Tether directly held approximately $98.5 billion in U.S. Treasury bills, representing 1.6% of all outstanding Treasury bills, making it one of the largest non-sovereign buyers in this crucial asset class, on par with nation-state-level investors. This paper investigates how Tether's market share of U.S. T…

Fluctuations around Turbulence Models
Flavio Tuteri, Alexandros Alexakis, Sergio Chibbaro
https://arxiv.org/abs/2507.17575 https://arxiv.org/pdf/2507.17575…

Fluctuations around Turbulence Models
Numerical simulations of turbulent flows at realistic Reynolds numbers generally rely on filtering out small scales from the Navier Stokes equations and modeling their impact through the Reynolds stress tensor $τ_{ij}$. Traditional models approximate $τ_{ij}$ solely as a function of the filtered velocity gradient, leading to deterministic subgrid scale closures. However, small scale fluctuations can locally exhibit instantaneous values whose deviation from the mean can have a significant infl…

Series A, Episode 06 - Seek-Locate-Destroy
RAI: Yes, Supreme Commander.
SERVALAN: Let them know, too, that any lack of cooperation, any hesitation in responding to an order, will be treated as mutiny. Let them know I have said this. Dismissed. [Rai clicks his heels and exits. There is a bleep from the comm. Servalan ignores it, looking pensive. The comm bleeps again and Servalan reacts this time.]

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI
Ryota Okumura, Tadahiro Taniguchi, Akira Taniguchi, Yoshinobu Hagiwara
https://arxiv.org/abs/2506.15468

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI
We propose co-creative learning as a novel paradigm where humans and AI, i.e., biological and artificial agents, mutually integrate their partial perceptual information and knowledge to construct shared external representations, a process we interpret as symbol emergence. Unlike traditional AI teaching based on unilateral knowledge transfer, this addresses the challenge of integrating information from inherently different modalities. We empirically test this framework using a human-AI interacti…

Unveiling Political Influence Through Social Media: Network and Causal Dynamics in the 2022 French Presidential Election
Ixandra Achitouv, David Chavalarias
https://arxiv.org/abs/2506.16449

Unveiling Political Influence Through Social Media: Network and Causal Dynamics in the 2022 French Presidential Election
During the 2022 French presidential election, we collected daily Twitter messages on key topics posted by political candidates and their close networks. Using a data-driven approach, we analyze interactions among political parties, identifying central topics that shape the landscape of political debate. Moving beyond traditional correlation analyses, we apply a causal inference technique: Convergent Cross Mapping, to uncover directional influences among political communities, revealing how some…