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explainable ai

2,878 papers

#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3

Experimenting with Multi-Agent Software Development: Towards a Unified Platform

A unified platform that utilizes multiple artificial intelligence agents to automate the process of transforming user requirements into well-organized deliverables, including user stories, prioritization, and UML sequence diagrams, along with the modular approach to APIs, unit tests, and end-to-end tests.

Malik Abdul Sami, Muhammad Waseem, Z. Rasheed et al. · 14 citations · ⚡1
#computer vision Apr 2024

Prioritizing Software Requirements Using Large Language Models

A web-based software tool utilizing AI agents and prompt engineering to automate task prioritization and apply diverse prioritization techniques, aimed at enhancing project management within the agile framework is introduced.

Malik Abdul Sami, Z. Rasheed, Muhammad Waseem et al. · 15 citations
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Aug 2024

AI based Multiagent Approach for Requirements Elicitation and Analysis

Results corroborate the effectiveness of LLMs in improving and streamlining RE phases by analyzing the semantic similarity and API performance of different models, as well as their effectiveness and efficiency in requirements analysis.

Malik Abdul Sami, Muhammad Waseem, Zheying Zhang et al. · 17 citations · ⚡2
#computer vision Apr 2024

Large Language Model Evaluation Via Multi AI Agents: Preliminary results

A novel multi-agent AI model is introduced that aims to assess and compare the performance of various LLMs, and initial results indicate that the GPT-3.5 Turbo model's performance is comparatively better than the other models.

Z. Rasheed, Muhammad Waseem, Kari Systä et al. · 23 citations
#computer vision Review Dec 2025

Vibe Coding in Practice: Flow, Technical Debt, and Guidelines for Sustainable Use

This article analyzes the flow-debt tradeoffs associated with VC and identifies and explains how current model, platform, and hardware limitations contribute to these issues, and proposes countermeasures to address them, informing research and practice towards more sustainable VC approaches.

Muhammad Waseem, Aakash Ahmad, Kai-Kristian Kemell et al. · 4 citations
#computer vision Review 2026

Generative AI Adoption in an Energy Company: Exploring Challenges and Use Cases

This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.

Malik Abdul Sami, Z. Rasheed, Meri Olenius et al. · 0 citations
#computer vision Review Feb 2026

Identifying and Prioritizing Generative AI Use Cases in an Organization: An Industrial Case Study

This study investigates how employees in a energy company understand AI adoption and identifies areas where AI and LLMs-based agentic workflows could assist daily activities, including reporting work, forecasting, data handling, maintenance-related tasks, and anomaly detection.

Malik Abdul Sami, Z. Rasheed, Meri Olenius et al. · 0 citations

From tech blogs

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Microsoft Research Blog Nov 5, 2026

Formally verifying agent-written full-stack web apps with PDD Kit

AI agents can generate code at a scale that’s hard for humans to review line-by-line. PDD Kit helps ensure the code is doing what the developer intended by creating formal specifications and testing against them. It converts developer intent into a Verus specification, proves AI-generated code meets it for every input, and uses tests where proofs aren't practical. Developers review intent, not every line. The post Formally verifying agent-written full-stack web apps with PDD Kit appeared first o…

Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

GPT-Lab Nov 3, 2026

Sovereignty Is the Option to Leave

Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.

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