Every paper checked — nothing hidden

All papers

Every paper checked in the week of 19–25 Oct 2026 · AI safety and reliability in deployment — nothing is hidden. Brief papers first.

PaperTopicRelevanceFeedback
A Survey on IEEE 802.11bn Wi-Fi 8: Advantages of Ultra High Reliability for Next-Generation Wireless LANs
Surveys physical and media access control layer enhancements in the IEEE 802.11bn Wi-Fi 8 standard for ultra-high reliability applications.
Peer-reviewed
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Surveys Wi-Fi wireless networking standards, not AI safety or model deployment reliability.
Hybrid AI and Computer Vision Framework for PCB/SMD Defect Detection with GUI-Enabled IoT Deployment
Combines YOLO architectures, attention mechanisms, and classical computer vision features to detect defects on printed circuit boards.
Peer-reviewedOlder paper (2026)
Older paper (2026) — discussed this week
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Presents industrial defect detection for PCBs, not AI safety, guardrails, or alignment.
The Infeasibility of Quantifying the Reliability of Life-Critical Real-Time Software
Argues that statistical methods cannot practically quantify the reliability of life-critical software due to required testing volume.
Peer-reviewed
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Discusses traditional real-time software reliability theory, not AI or machine learning systems.
WIP: Active Learning Through Prompt Engineering and Agentic AI Simulation-A Pilot Project in Computer Networks Education
Simulates classroom interactions using multiple language model agents configured to support student learning in computer networks education.
Peer-reviewedOlder paper (2024)
Older paper (2024) — discussed this week
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Covers classroom simulation for education, not AI safety, jailbreaks, or deployment guardrails.
Landscape and Taxonomy of Prompt Engineering Patterns in Software Engineering
Surveys and categorizes prompt engineering patterns used to improve large language model performance in software engineering tasks.
Peer-reviewedOlder paper (2025)
Older paper (2025) — discussed this week
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Surveys general prompt engineering patterns for software engineering, not safety or guardrails.
Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection
Injects model-predictive control disturbances into expert robot demonstrations to train imitation learning policies that recover safely from errors.
Peer-reviewedOlder paper (2025)
Older paper (2025) — discussed this week
AI safety and reliability in deployment
via ieee · 19 Oct, 06:19
Not relevant
Addresses physical robotic control safety rather than AI system safety and reliability deployment.
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