Cover Image

Can LLMs Solve Science or Just Write Code? Evaluating Quantum Solver Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Baresi, Luciano, Bianculli, Domenico, Ernzer, Maryse, Lestingi, Livia, Pastore, Fabrizio, Shin, Seung Yeob
Format:	Preprint
Published:	2026
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Randomized and Diverse Input State Generation for Quantum Program Testing
by: Ernzer, Maryse, et al.
Published: (2026)

Quantum Program Linting with LLMs: Emerging Results from a Comparative Study
by: Shin, Seung Yeob, et al.
Published: (2025)

Towards Generating Executable Metamorphic Relations Using Large Language Models
by: Shin, Seung Yeob, et al.
Published: (2024)

Beyond Rules: LLM-Powered Linting for Quantum Programs
by: Cassieri, Pietro, et al.
Published: (2026)

Testing CPS with Design Assumptions-Based Metamorphic Relations and Genetic Programming
by: Mandrioli, Claudio, et al.
Published: (2024)

Stress Testing Control Loops in Cyber-Physical Systems
by: Mandrioli, Claudio, et al.
Published: (2023)

Can LLMs Generate User Stories and Assess Their Quality?
by: Quattrocchi, Giovanni, et al.
Published: (2025)

A Piece of QAICCC: Towards a Countermeasure Against Crosstalk Attacks in Quantum Servers
by: Marquer, Yoann, et al.
Published: (2025)

Towards a Taxonomy of Software Log Smells
by: Saarimäki, Nyyti, et al.
Published: (2024)

Rigorous Assessment of Model Inference Accuracy using Language Cardinality
by: Clun, Donato, et al.
Published: (2022)

Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction
by: Hadadi, Fatemeh, et al.
Published: (2023)

Towards an Agentic LLM-based Approach to Requirement Formalization from Unstructured Specifications
by: Tagliaferro, Alberto, et al.
Published: (2026)

Impact of Log Parsing on Deep Learning-Based Anomaly Detection
by: Khan, Zanis Ali, et al.
Published: (2023)

Automated Detection and Mitigation of Dependability Failures in Healthcare Scenarios through Digital Twins
by: Guindani, Bruno, et al.
Published: (2026)

Learning-Guided Fuzzing for Testing Stateful SDN Controllers
by: Ollando, Raphaël, et al.
Published: (2024)

Diagnosing Violations of State-based Specifications in iCFTL
by: Stratan, Cristina, et al.
Published: (2025)

Test Schedule Generation for Acceptance Testing of Mission-Critical Satellite Systems
by: Ollando, Raphaël, et al.
Published: (2025)

LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs
by: Hadadi, Fatemeh, et al.
Published: (2024)

Trace Diagnostics for Signal-based Temporal Properties
by: Boufaied, Chaima, et al.
Published: (2022)

When LLMs Meet API Documentation: Can Retrieval Augmentation Aid Code Generation Just as It Helps Developers?
by: Chen, Jingyi, et al.
Published: (2025)

CodeAD: Synthesize Code of Rules for Log-based Anomaly Detection with LLMs
by: Huang, Junjie, et al.
Published: (2025)

A Machine Learning Approach for Automated Filling of Categorical Fields in Data Entry Forms
by: Belgacem, Hichem, et al.
Published: (2022)

Learning-Based Relaxation of Completeness Requirements for Data Entry Forms
by: Belgacem, Hichem, et al.
Published: (2023)

How Toxic Can You Get? Search-based Toxicity Testing for Large Language Models
by: Corbo, Simone, et al.
Published: (2025)

SAGA: Detecting Security Vulnerabilities Using Static Aspect Analysis
by: Marquer, Yoann, et al.
Published: (2026)

GDPR-Relevant Privacy Concerns in Mobile Apps Research: A Systematic Literature Review
by: Cejas, Orlando Amaral, et al.
Published: (2024)

Fuzzing-based Mutation Testing of C/C++ Software in Cyber-Physical Systems
by: Lee, Jaekwon, et al.
Published: (2025)

Can Language Models Pretend Solvers? Logic Code Simulation with LLMs
by: Chen, Minyu, et al.
Published: (2024)

GAN-enhanced Simulation-driven DNN Testing in Absence of Ground Truth
by: Attaoui, Mohammed, et al.
Published: (2025)

Mutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs
by: Li, Ziyu, et al.
Published: (2024)

Search-based DNN Testing and Retraining with GAN-enhanced Simulations
by: Attaoui, Mohammed Oualid, et al.
Published: (2024)

Testing Updated Apps by Adapting Learned Models
by: Ngo, Chanh-Duc, et al.
Published: (2023)

A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection
by: Ali, Shan, et al.
Published: (2023)

Field-based Security Testing of SDN configuration Updates
by: Malik, Jahanzaib, et al.
Published: (2024)

Can LLMs Write CI? A Study on Automatic Generation of GitHub Actions Configurations
by: Ghaleb, Taher A., et al.
Published: (2025)

MOTIF: A tool for Mutation Testing with Fuzzing
by: Lee, Jaekwon, et al.
Published: (2024)

Learning Failure-Inducing Models for Testing Software-Defined Networks
by: Ollando, Raphaël, et al.
Published: (2022)

MathDuels: Evaluating LLMs as Problem Posers and Solvers
by: Xu, Zhiqiu, et al.
Published: (2026)

BOOP: Write Right Code
by: Goenka, Vaani, et al.
Published: (2025)

Write Your Own CodeChecker: An Automated Test-Driven Checker Development Approach with LLMs
by: Liu, Jun, et al.
Published: (2024)