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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.LG2026

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms

Umid Suleymanov, Ilhama Novruzova, Khalid Mammadov +2

The paper studies how fairness-enhancing algorithms affect membership inference privacy risks across different subpopulations, revealing that privacy impacts vary with model type,…

cs.CR2026

GitInject: Real-World Prompt Injection Attacks in AI-Powered CI/CD Pipelines

Jafar Isbarov, Umid Suleymanov, Ilia Shumailov +1

AI-powered agents are increasingly embedded in continuous integration and continuous delivery/deployment (CI/CD) pipelines to autonomously review pull requests (PRs), triage issues…

cs.LG2026

Robust and Explainable Divide-and-Conquer Learning for Intrusion Detection

Yan Zhou, Kevin Hamlen, Michael De Lucia +5

Machine learning-based intrusion detection requires complex models to capture patterns in high-dimensional, noisy, and class-imbalanced raw network traffic, yet deploying such mode…

cs.CV2026

SPRINT: Semi-supervised Prototypical Representation for Few-Shot Class-Incremental Tabular Learning

Umid Suleymanov, Murat Kantarcioglu, Kevin S Chan +6

Real-world systems must continuously adapt to novel concepts from limited data without forgetting previously acquired knowledge. While Few-Shot Class-Incremental Learning (FSCIL) i…

cs.AI2026

Beyond Refusal: Probing the Limits of Agentic Self-Correction for Semantic Sensitive Information

Umid Suleymanov, Zaur Rajabov, Emil Mirzazada +1

While defenses for structured PII are mature, Large Language Models (LLMs) pose a new threat: Semantic Sensitive Information (SemSI), where models infer sensitive identity attribut…

cs.DB2025

NOMAD -- Navigating Optimal Model Application to Datastreams

Ashwin Gerard Colaco, Sharad Mehrotra, Michael J De Lucia +5

NOMAD (Navigating Optimal Model Application for Datastreams) is an intelligent framework for data enrichment during ingestion that optimizes realtime multiclass classification by d…