{"total":45,"rows":[{"id":"2105.01984","title":"Software Engineering for AI-Based Systems: A Survey","created":"2021-05-05","cited_by_count":69,"area":null},{"id":"2110.10234","title":"Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process","created":"2021-10-19","cited_by_count":56,"area":null},{"id":"2308.03656","title":"Emotionally Numb or Empathetic? Evaluating How LLMs Feel Using EmotionBench","created":"2023-08-07","cited_by_count":54,"area":null},{"id":"2304.00078","title":"A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners","created":"2023-03-31","cited_by_count":22,"area":null},{"id":"2312.06056","title":"METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities","created":"2023-12-11","cited_by_count":20,"area":null},{"id":"2305.12751","title":"Testing of Deep Reinforcement Learning Agents with Surrogate Models","created":"2023-05-22","cited_by_count":13,"area":null},{"id":"2303.07476","title":"Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision","created":"2023-03-13","cited_by_count":11,"area":null},{"id":"2401.03188","title":"A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence","created":"2024-01-06","cited_by_count":10,"area":null},{"id":"2105.08095","title":"Automatic Fault Detection for Deep Learning Programs Using Graph Transformations","created":"2021-05-17","cited_by_count":9,"area":null},{"id":"2310.01765","title":"Data Cleaning and Machine Learning: A Systematic Literature Review","created":"2023-10-03","cited_by_count":9,"area":null},{"id":"2402.00699","title":"PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software","created":"2024-02-01","cited_by_count":9,"area":null},{"id":"2405.03727","title":"Large Language Models Synergize with Automated Machine Learning","created":"2024-05-06","cited_by_count":9,"area":null},{"id":"2404.00897","title":"Machine Learning Robustness: A Primer","created":"2024-04-01","cited_by_count":8,"area":null},{"id":"2208.08982","title":"Quality issues in Machine Learning Software Systems","created":"2022-08-18","cited_by_count":7,"area":null},{"id":"2201.12428","title":"Systematic Training and Testing for Machine Learning Using Combinatorial Interaction Testing","created":"2022-01-28","cited_by_count":6,"area":null},{"id":"2307.11525","title":"Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development","created":"2023-07-21","cited_by_count":6,"area":null},{"id":"2401.03069","title":"Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study","created":"2024-01-05","cited_by_count":6,"area":null},{"id":"2404.08517","title":"Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward","created":"2024-04-12","cited_by_count":6,"area":null},{"id":"2408.06226","title":"A Large-Scale Study of Model Integration in ML-Enabled Software Systems","created":"2024-08-12","cited_by_count":6,"area":null},{"id":"2404.17871","title":"Deep Learning Library Testing: Definition, Methods and Challenges","created":"2024-04-27","cited_by_count":5,"area":null},{"id":"2408.09196","title":"Maintainability Challenges in ML: A Systematic Literature Review","created":"2024-08-17","cited_by_count":5,"area":null},{"id":"2203.10384","title":"Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems","created":"2022-03-19","cited_by_count":4,"area":null},{"id":"2106.05549","title":"Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis","created":"2021-06-10","cited_by_count":3,"area":null},{"id":"2204.13963","title":"Tailored Uncertainty Estimation for Deep Learning Systems","created":"2022-04-29","cited_by_count":3,"area":null},{"id":"2207.06282","title":"DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment","created":"2022-07-13","cited_by_count":3,"area":null},{"id":"2207.11976","title":"Differential testing for machine learning: an analysis for classification algorithms beyond deep learning","created":"2022-07-25","cited_by_count":3,"area":null},{"id":"2310.10665","title":"Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey","created":"2023-09-19","cited_by_count":3,"area":null},{"id":"2112.15277","title":"Machine Learning Application Development: Practitioners' Insights","created":"2021-12-31","cited_by_count":2,"area":null},{"id":"2202.12139","title":"Testing Deep Learning Models: A First Comparative Study of Multiple Testing Techniques","created":"2022-02-24","cited_by_count":2,"area":null},{"id":"2204.00694","title":"Testing Feedforward Neural Networks Training Programs","created":"2022-04-01","cited_by_count":2,"area":null},{"id":"2303.01998","title":"MLTEing Models: Negotiating, Evaluating, and Documenting Model and System Qualities","created":"2023-03-03","cited_by_count":2,"area":null},{"id":"2404.09384","title":"Generative transformations and patterns in LLM-native approaches for software verification and falsification","created":"2024-04-14","cited_by_count":2,"area":null},{"id":"2105.01407","title":"A Review on Oracle Issues in Machine Learning","created":"2021-05-04","cited_by_count":1,"area":null},{"id":"2310.03620","title":"PeaTMOSS: Mining Pre-Trained Models in Open-Source Software","created":"2023-10-05","cited_by_count":1,"area":null},{"id":"2311.00801","title":"GIST: Generated Inputs Sets Transferability in Deep Learning","created":"2023-11-01","cited_by_count":1,"area":null},{"id":"2404.05622","title":"How to Evaluate Entity Resolution Systems: An Entity-Centric Framework with Application to Inventor Name Disambiguation","created":"2024-04-08","cited_by_count":1,"area":null},{"id":"2105.01404","title":"TimeGym: Debugging for Time Series Modeling in Python","created":"2021-05-04","cited_by_count":0,"area":null},{"id":"2111.14324","title":"Is the Rush to Machine Learning Jeopardizing Safety? Results of a Survey","created":"2021-11-29","cited_by_count":0,"area":null},{"id":"2306.15007","title":"Quality Issues in Machine Learning Software Systems","created":"2023-06-26","cited_by_count":0,"area":null},{"id":"2310.18987","title":"Path Analysis for Effective Fault Localization in Deep Neural Networks","created":"2023-10-29","cited_by_count":0,"area":null},{"id":"2406.08575","title":"Using Quality Attribute Scenarios for ML Model Test Case Generation","created":"2024-06-12","cited_by_count":0,"area":null},{"id":"2410.05819","title":"CAP: Detecting Unauthorized Data Usage in Generative Models via Prompt Generation","created":"2024-10-08","cited_by_count":0,"area":null},{"id":"2504.11079","title":"Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2507.08908","title":"The Engineer's Dilemma: A Review of Establishing a Legal Framework for Integrating Machine Learning in Construction by Navigating Precedents and Industry Expectations","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2608.03489","title":"Leveraging System-Level Observations to Inform Bayesian Learning of Model Parameters for Quantitative Verification","created":"2026-08-04","cited_by_count":0,"area":null}],"next_cursor":null}