Tootfinder

"Whoever needs to see it, will see it": Motivations and Labor of Creating Algorithmic Conspirituality Content on TikTok
Ankolika De, Kelley Cotter, Shaheen Kanthawala, Haley McAtee, Amy Ritchart, Gahana Kadur
https://arxiv.org/abs/2506.16851

"Whoever needs to see it, will see it": Motivations and Labor of Creating Algorithmic Conspirituality Content on TikTok
Recent studies show that users often interpret social media algorithms as mystical or spiritual because of their unpredictability. This invites new questions about how such perceptions affect the content that creators create and the communities they form online. In this study, 14 creators of algorithmic conspirituality content on TikTok were interviewed to explore their interpretations and creation processes influenced by the platform's For You Page algorithm. We illustrate how creators' belief…

Evaluating the Use of LLMs for Documentation to Code Traceability
Ebube Alor, SayedHassan Khatoonabadi, Emad Shihab
https://arxiv.org/abs/2506.16440 https:…

Evaluating the Use of LLMs for Documentation to Code Traceability
Large Language Models (LLMs) offer new potential for automating documentation-to-code traceability, yet their capabilities remain underexplored. We present a comprehensive evaluation of LLMs (Claude 3.5 Sonnet, GPT-4o, and o3-mini) in establishing trace links between various software documentation (including API references and user guides) and source code. We create two novel datasets from two open-source projects (Unity Catalog and Crawl4AI). Through systematic experiments, we assess three key…

Low-Energy Supernova Constraints on Lepton Flavor Violating Axions
Zi-Miao Huang, Zuowei Liu
https://arxiv.org/abs/2506.16922 https://

Low-Energy Supernova Constraints on Lepton Flavor Violating Axions
The extreme conditions within the supernova core, a high-temperature and high-density environment, create an ideal laboratory for the search for new physics beyond the Standard Model. Of particular interest are low-energy supernovae, characterized by their low explosion energies, which place strong constraints on the new-physics energy transfer from the core to the mantle. We compute low-energy supernova constraints on lepton-flavor-violating axions and axion-like particles that couple to both …

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI
Marcelle Momha
https://arxiv.org/abs/2506.13818 https://arxiv.org/pdf…

The Synthetic Mirror -- Synthetic Data at the Age of Agentic AI
Synthetic data, which is artificially generated and intelligently mimicking or supplementing the real-world data, is increasingly used. The proliferation of AI agents and the adoption of synthetic data create a synthetic mirror that conceptualizes a representation and potential distortion of reality, thus generating trust and accountability deficits. This paper explores the implications for privacy and policymaking stemming from synthetic data generation, and the urgent need for new policy inst…

This https://arxiv.org/abs/2506.04929 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
Neural Machine Translation (NMT) has improved translation by using Transformer-based models, but it still struggles with word ambiguity and context. This problem is especially important in domain-specific applications, which often have problems with unclear sentences or poor data quality. Our research explores how adding information to models can improve translations in the context of e-commerce data. To this end we create ConECT -- a new Czech-to-Polish e-commerce product translation dataset c…

This https://arxiv.org/abs/2309.05901 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters
In this paper, we study the concurrent composition of interactive mechanisms with adaptively chosen privacy-loss parameters. In this setting, the adversary can interleave queries to existing interactive mechanisms, as well as create new ones. We prove that every valid privacy filter and odometer for noninteractive mechanisms extends to the concurrent composition of interactive mechanisms if privacy loss is measured using $(ε, δ)$-DP, $f$-DP, or Rényi DP of fixed order. Our results offer stro…

This https://arxiv.org/abs/2409.19080 has been replaced.
link: https://scholar.google.com/scholar?q=a

Stimulated Raman Spectroscopy with Tunable Visible Broadband Probe Pulse Generated by Kerr-Instability Amplification
Femtosecond, broadband stimulated Raman spectroscopy is a popular approach to measuring molecular dynamics with excellent signal-to-noise and spectral resolution. We present a new method for broadband stimulated Raman spectroscopy that employs Kerr-instability amplification to amplify the supercontinuum spectrum from sapphire and create a highly tunable Raman probe spectrum spanning from 530 to 1000 nm (-6000 to 2800 cm^(-1)). Our method, called Kerr-instability amplification for broadband stim…

MathPartner is a breakthrough technology for natural sciences education, scientic and engineering applications
Gennadi Malaschonok, Roman Sakh
https://arxiv.org/abs/2505.03740

MathPartner is a breakthrough technology for natural sciences education, scientic and engineering applications
The article provides a brief description of the MathPartner service. This freely available cloud-based Mathematics is a universal system for symbolic-numeric calculations. Its Mathpar language is a subset of the LaTeX language, but allows you to create mathematical texts that contain "computable" mathematical operators. This opens up completely new opportunities for improving the educational process for all natural science disciplines, for the use of mathematics in scientific and engineering ca…

This https://arxiv.org/abs/2404.18445 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

AI and the Dynamic Supply of Training Data
Artificial intelligence (AI) systems rely heavily on human-generated data, yet the people behind that data are often overlooked. Human behavior can play a major role in AI training datasets, be it in limiting access to existing works or in deciding which types of new works to create or whether to create any at all. We examine creators' behavioral change when their works become training data for commercial AI. Specifically, we focus on contributors on Unsplash, a popular stock image platform wit…

Taxonomy of migration scenarios for Qiskit refactoring using LLMs
Jos\'e Manuel Su\'arez, Lu\'is Mariano Bibb\'o, Joaqu\'in Bogado, Alejandro Fernandez
https://arxiv.org/abs/2506.07135

Taxonomy of migration scenarios for Qiskit refactoring using LLMs
As quantum computing advances, quantum programming libraries' heterogeneity and steady evolution create new challenges for software developers. Frequent updates in software libraries break working code that needs to be refactored, thus adding complexity to an already complex landscape. These refactoring challenges are, in many cases, fundamentally different from those known in classical software engineering due to the nature of quantum computing software. This study addresses these challenges b…

RESOLVE: Rare Event Surrogate Likelihood for Gravitational Wave Paleontology Parameter Estimation
Ann-Kathrin Schuetz, Alexander Migala, Adam Boesky, Alan W. P. Poon, Floor S. Broekgaarden, Aobo Li
https://arxiv.org/abs/2506.00757

RESOLVE: Rare Event Surrogate Likelihood for Gravitational Wave Paleontology Parameter Estimation
The first detection of gravitational waves, recognized by the 2017 Nobel Prize in Physics, has opened up a new research field: gravitational-wave paleontology. When massive stars evolve into black holes and collide, they create gravitational waves that propagate through space and time. These gravitational-waves, now detectable on Earth, act as fossils tracing the histories of the massive stars that created them. Estimating physics parameters of these massive stars from detected gravitational-wa…

Does Trump's Tariff Make America Great Again? An Empirical Analysis of US-China Trade War Impact on American Business Formation (2018-2025)
Ruiming Min
https://arxiv.org/abs/2506.00999

Does Trump's Tariff Make America Great Again? An Empirical Analysis of US-China Trade War Impact on American Business Formation (2018-2025)
This study examines whether Donald Trump's tariff policies, particularly the US-China trade war initiated in 2018, delivered on promises to revitalize American manufacturing and create jobs. Using county-level business application data from 2018-2025, we analyze the relationship between tariff implementation and new business formation through linear regression analysis. Our findings reveal a statistically significant positive association between US tariffs on China and American business applica…