Tootfinder

On the need to perform comprehensive evaluations of automated program repair benchmarks: Sorald case study
Sumudu Liyanage, Sherlock A. Licorish, Markus Wagner, Stephen G. MacDonell
https://arxiv.org/abs/2508.15135

On the need to perform comprehensive evaluations of automated program repair benchmarks: Sorald case study
In supporting the development of high-quality software, especially necessary in the era of LLMs, automated program repair (APR) tools aim to improve code quality by automatically addressing violations detected by static analysis profilers. Previous research tends to evaluate APR tools only for their ability to clear violations, neglecting their potential introduction of new (sometimes severe) violations, changes to code functionality and degrading of code structure. There is thus a need for res…

Quantum Portfolio Optimization: An Extensive Benchmark
Eric Stopfer, Friedrich Wagner
https://arxiv.org/abs/2509.17876 https://arxiv.org/pdf/2509.17876

Quantum Portfolio Optimization: An Extensive Benchmark
Recently, several researchers proposed portfolio optimization as a potential use case for quantum optimization. However, the literature is lacking an extensive benchmark quantifying the potential of quantum computers for portfolio optimization. In this work, we fill this gap. We provide a computational study, comparing quantum approaches against state-of-the-art classical methods on a meaningful, real-world instance set. In particular, we compare quantum annealing and the quantum approximate op…

A Tensor Network Framework for Lindbladian Spectra and Steady States
Philipp Westhoff, Mattia Moroder, Ulrich Schollw\"ock, Sebastian Paeckel
https://arxiv.org/abs/2509.07709

A Tensor Network Framework for Lindbladian Spectra and Steady States
Quantum systems coupled to (non-)Markovian environments attract increasing attention due to their peculiar physical properties. Exciting prospects such as unconventional non-equilibrium phases beyond the Mermin-Wagner limit, or the environment-assisted, robust preparation of highly entangled states, demand a systematic analysis of quantum many-body phases out of equilibrium. Akin to the equilibrium case, this requires the computation of the low-lying eigenstates of Lindbladians, a problem chall…

Learning from Convenience Samples: A Case Study on Fine-Tuning LLMs for Survey Non-response in the German Longitudinal Election Study
Tobias Holtdirk, Dennis Assenmacher, Arnim Bleier, Claudia Wagner
https://arxiv.org/abs/2509.25063

Learning from Convenience Samples: A Case Study on Fine-Tuning LLMs for Survey Non-response in the German Longitudinal Election Study
Survey researchers face two key challenges: the rising costs of probability samples and missing data (e.g., non-response or attrition), which can undermine inference and increase the use of convenience samples. Recent work explores using large language models (LLMs) to simulate respondents via persona-based prompts, often without labeled data. We study a more practical setting where partial survey responses exist: we fine-tune LLMs on available data to impute self-reported vote choice under bot…