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ORCIDCAIN 2025: Ottawa, ON, Canada
- 4th IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2025, Ottawa, ON, Canada, April 27-28, 2025. IEEE 2025, ISBN 979-8-3315-0219-5
- Evangelos Ntentos, Stephen John Warnett, Uwe Zdun:
Rule-Based Assessment of Reinforcement Learning Practices Using Large Language Models. 1-11 - Mateus Devino, Evaline Ju, Paulo Marques Caldeira Junior:
Designing and Implementing LLM Guardrails Components in Production Environments. 12-17 - Alina Mailach, Sebastian Simon, Johannes Dorn, Norbert Siegmund:
Themes of Building LLM-Based Applications for Production: A Practitioner's View. 18-30 - Maryam Ekhlasi, Anurag Prakash, Maxime Lamothe, Michel R. Dagenais:
InsightAI: Root Cause Analysis in Large Log Files with Private Data Using Large Language Model. 31-41 - Hui Song, Arda Goknil, Xiaojun Jiang, Espen Melum, Hyunwhan Joe, Caterina Gazzotti, Valerio Frascolla, Adela Nedisan Videsjorden, Phu Nguyen:
Developing Multi-Agent LLM Applications Through Continuous Human-LLM Co-Programming. 42-47 - Shreyas Kumar Parida, Ilias Gerostathopoulos
, Justus Bogner:
How Do Model Export Formats Impact the Development of ML-Enabled Systems? A Case Study on Model Integration. 48-59 - Shangeetha Sivasothy, Scott Barnett, Stefanus Kurniawan, Zafaryab Rasool, Rajesh Vasa:
RAGProbe: Breaking RAG Pipelines with Evaluation Scenarios. 60-71 - Vince Nguyen, Vidya Dhopate, Hieu Trung Huynh, Hiba Bouhlal, Anusha Annengala, Gian Luca Scoccia, Matias Martinez, Vincenzo Stoico, Ivano Malavolta:
On-Device or Remote? On the Energy Efficiency of Fetching LLM-Generated Content. 72-82 - Kritin Maddireddy, Santhosh Kotekal Methukula, Chandrasekar Sridhar, Karthik Vaidhyanathan:
LoCoML: A Framework for Real-World ML Inference Pipelines. 83-88 - Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos, Petr Hnetynka, Tomás Bures, Gerard Pons, Besim Bilalli, Anna Queralt:
Towards Continuous Experiment-Driven MLOps. 89-94 - Sergio Morales, Robert Clarisó, Jordi Cabot:
ImageBiTe: A Framework for Evaluating Representational Harms in Text-to-Image Models. 95-106 - Chandrasekar Sridhar, Vyakhya Gupta, Prakhar Jain, Karthik Vaidhyanathan:
Approach Towards Semi-Automated Certification of Low Criticality ML-Enabled Airborne Applications. 107-112 - Yining Hong, Christopher Steven Timperley, Christian Kästner:
From Hazard Identification to Controller Design: Proactive and LLM-Supported Safety Engineering for ML-Powered Systems. 113-118 - Niels With Mikkelsen, Lasse Steen Pedersen, Mansoor Hussain, Victor Foged, Ekkart Kindler:
Bringing Machine Learning Models Beyond the Experimental Stage with Explainable AI. 119-129 - Richard Nordsieck, Jan-Philipp Steghöfer, Manish Bhandari:
Challenges in AI Projects for Machinery and Plant Engineering. 130-131 - Razan Abualsaud:
Towards a Domain-Specific Modeling Language for Streamlined Change Management in AI Systems Development. 132-137 - Hamed Barzamini, Fatemeh Nazaritiji, Annalise Brockmann, Hasan Ferdowsi, Mona Rahimi:
An AI-driven Requirements Engineering Framework Tailored for Evaluating AI-Based Software. 138-149 - Karthik Shivashankar, Antonio Martini:
MLScent: A Tool for Anti-Pattern Detection in ML Projects. 150-160 - Boyue Caroline Hu, Divya Gopinath, Corina S. Pasareanu, Nina Narodytska, Ravi Mangal, Susmit Jha:
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study). 161-172 - Rodrigo Ximenes, Antonio Pedro Santos Alves, Tatiana Escovedo, Rodrigo O. Spínola, Marcos Kalinowski:
Investigating Issues That Lead to Code Technical Debt in Machine Learning Systems. 173-183 - Santiago del Rey, Adrià Medina, Xavier Franch, Silverio Martínez-Fernández:
Addressing Quality Challenges in Deep Learning: The Role of MLOps and Domain Knowledge. 184-189 - Jinyang Li, Sangwon Hyun, M. Ali Babar:
DDPT: Diffusion-Driven Prompt Tuning for Large Language Model Code Generation. 190-200 - Kannan Parthasarathy, Karthik Vaidhyanathan, Rudra Dhar, Venkat Krishnamachari, Adyansh Kakran, Sreemaee Akshathala, Shrikara Arun, Amey Karan, Basil Muhammed, Sumant Dubey, Mohan Veerubhotla:
Engineering LLM Powered Multi-Agent Framework for Autonomous CloudOps. 201-211 - Lynn Vonderhaar, Timothy Elvira, Omar Ochoa:
Generating and Verifying Synthetic Datasets with Requirements Engineering. 212-221 - Oluwafemi Odu, Alvine Boaye Belle, Song Wang:
LLM-Based Safety Case Generation for Baidu Apollo: Are We there Yet? 222-233 - Dan Liyanage, Mahshid Moha, Sandy Suresh:
SqPal - Text to SQL GenAI Tool for PayPal. 234-235 - Keerthiga Rajenthiram:
Optimizing Data Analytics Workflows Through User-Driven Experimentation: Progress and Updates. 236-240 - Aidin Azamnouri:
CoCo Challenges in ML Engineering Teams: How to Collaboratively Build ML-Enabled Systems. 241-243 - Yorick Sens:
Towards a Privacy-by-Design Framework for ML-Enabled Systems. 244-246 - Marvin Muñoz Barón:
Towards an Adoption Framework to Foster Trust in AI-Assisted Software Engineering. 247-249 - Joshua Owotogbe:
Assessing and Enhancing the Robustness of LLM-Based Multi-Agent Systems Through Chaos Engineering. 250-252 - Rumbidzai Chitakunye:
Designing ML-Enabled Software Systems with ML Model Composition: A Green AI Perspective. 253-255 - Renato Cordeiro Ferreira:
A Metrics-Oriented Architectural Model to Characterize Complexity on Machine Learning-Enabled Systems. 256-260 - Shamse Tasnim Cynthia:
Identification and Optimization of Redundant Code Using Large Language Models. 261-263 - Hasan Kaplan:
Systematic Testing of Security-Related Vulnerabilities in LLM-Based Applications. 264-266 - Hadiza Umar Yusuf:
Model-Based Verification for AI-Enabled Cyber-Physical Systems Through Guided Falsification of Temporal Logic Properties. 267-269 - Merel Veracx:
A Holistic Framework for Evolving AI-Based Systems. 270-272 - Benjamin Weigel, Fabian Stieler, Bernhard Bauer:
All You Need is an AI Platform: A Proposal for a Complete Reference Architecture. 273-274 - Hala Abdelkader, Mohamed Almorsy Abdelrazek, Sankhya Singh, Irini Logothetis, Priya Rani, Rajesh Vasa, Jean-Guy Schneider:
Safeguarding LLM-Applications: Specify or Train? 275-276 - Hadiza Umar Yusuf, Khouloud Gaaloul:
Navigating the Shift: Architectural Transformations and Emerging Verification Demands in AI-Enabled Cyber-Physical Systems. 277-278 - Orlando Marquez Ayala:
Task Decomposition and RAG as Design Patterns for LLM-Based Systems. 279-280 - Aftab Hussain, Md. Rafiqul Islam Rabin, Toufique Ahmed, Mohammad Amin Alipour, Bowen Xu, Stephen Huang:
Finding Trojan Triggers in Code LLMs: An Occlusion-Based Human-in-the-Loop Approach. 281-282 - Katherine R. Dearstyne, Pedro Alarcon Granadeno, Theodore Chambers, Jane Cleland-Huang:
Evaluating Reinforcement Learning Safety and Trustworthiness in Cyber-Physical Systems. 283-284 - Qiulu Peng, Chi Zhang, Ravi Mangal, Corina S. Pasareanu, Limin Jia:
Random Perturbation Attack on LLMs for Code Generation. 285-287
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