Every paper checked — nothing hidden
All papers
Every paper checked in the week of 19–25 Oct 2026 — nothing is hidden. Brief papers first.
All26In brief0More (on-topic)0Not relevant16Not assessed5Older19Could not confirm5Blogs with no paper40All blogs41
| Paper | Topic | Relevance | Feedback |
|---|---|---|---|
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | LLM evaluation and benchmarks via blog · 19 Oct, 06:19 | Not relevant The main contribution is a security assessment and red-teaming tool, fitting AI safety. | |
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | Multimodal models via blog · 19 Oct, 06:19 | Not relevant Targets text LLMs and dialogue probing, not multimodal models. | |
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | Small and efficient models via blog · 19 Oct, 06:19 | Not relevant Does not focus on model compression, quantization, or efficient serving. | |
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | AI agents via blog · 19 Oct, 06:19 | Not relevant Focuses on red-teaming LLMs, not multi-step agent planning or tool use. | |
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | LLMs for code via blog · 19 Oct, 06:19 | Not relevant Covers security vulnerability probing, not coding assistants or code generation. | |
| garak: A Framework for Security Probing Large Language Models Presents an open-source security probing framework to evaluate language models against adversarial attacks and identify vulnerabilities. PreprintOlder paper (2024) Older paper (2024) — discussed this week | Retrieval-augmented generation (RAG) via blog · 19 Oct, 06:19 | Not relevant Does not address retrieval-augmented generation or document grounding. | |
| 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. | |
| 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 | Computer vision for industrial applications via ieee · 19 Oct, 06:19 | Not relevant Concerns robotics imitation learning and control, not industrial vision or inspection. | |
| Multimodal Approaches for Efficient Evaluation of Handwritten Answer Scripts via Large Language Models Evaluates handwritten exam scripts using vision-language models and dynamic response fragmentation rather than traditional text recognition. Peer-reviewedOlder paper (2026) Older paper (2026) — discussed this week | Small and efficient models via ieee · 19 Oct, 06:18 | Not relevant Applies vision-language models to grading rather than efficient model compression or serving. | |
| Online Model Distillation for Efficient Video Inference Specializes compact video segmentation models on live camera streams by intermittently distilling knowledge from a larger teacher model. Peer-reviewedOlder paper (2018) Older paper (2018) — discussed this week | Multimodal models via ieee · 19 Oct, 06:18 | Not relevant Focuses on pure computer vision segmentation, not multimodal text-vision models. | |
| Online Model Distillation for Efficient Video Inference Specializes compact video segmentation models on live camera streams by intermittently distilling knowledge from a larger teacher model. Peer-reviewedOlder paper (2018) Older paper (2018) — discussed this week | Computer vision for industrial applications via ieee · 19 Oct, 06:18 | Not relevant Addresses video segmentation inference, not industrial defect detection or manufacturing. |
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