Here's your daily roundup of the most relevant AI and ML news for September 23, 2026. We're also covering 7 research developments. Click through to read the full articles from our curated sources.
Research & Papers
1. Semi-Automated Detection of Gaps in LLM Security Knowledge
arXiv:2607.18496v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM performance on security tasks is an active area of measurement and research, often with a focus on i...
Source: arXiv - AI | 10 hours ago
2. Dynamic Deep Prompt Optimization for Defending Against Jailbreak Attacks on LLMs
arXiv:2609.26185v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit harmful or unintended content. While model fine-tuning is an option for safety alignment, it is cos...
Source: arXiv - AI | 10 hours ago
3. On the Effect of Bit-Level Parameter Perturbations in Machine Learning and Deep Learning Models
arXiv:2609.26280v1 Announce Type: new Abstract: In this chapter, we investigate how classical machine learning models respond to small, targeted modifications in their parameters. We compare and contrast these results to analogous experiments on deep learning models. For classical learning model...
Source: arXiv - Machine Learning | 10 hours ago
4. FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in Federated Learning
arXiv:2502.16396v2 Announce Type: replace Abstract: Federated learning systems are increasingly threatened by data poisoning attacks, where malicious clients compromise global models by contributing tampered updates. Existing defenses often rely on impractical assumptions, such as access to a ce...
Source: arXiv - Machine Learning | 10 hours ago
5. Adversarial Course-of-Action Generation: Game-Theoretic Multi-Agent Algorithms for COA matching & COA generation
arXiv:2609.26059v1 Announce Type: new Abstract: Course-of-action (COA) generation is a distributed planning problem: a system must propose structured candidate actions, evaluate them against an adversarial response, and surface options that remain tactically coherent under changing conditions. W...
Source: arXiv - AI | 10 hours ago
6. Ultra Strong Machine Learning: LLM-Generated Explanations Do Not Yet Suffice for Teaching Humans Active Learning Strategy
arXiv:2509.00961v3 Announce Type: replace-cross Abstract: Active learning is a general learning mechanism shared by artificial and human learners. Whether AI can teach humans such a strategy that transfers across domains is an open question. Ultra Strong Machine Learning (USML), a system whose e...
Source: arXiv - Machine Learning | 10 hours ago
7. Potential for Enhanced Learning in Machine Learning Classes by Using Wiki LLM Indexing
arXiv:2609.25303v1 Announce Type: new Abstract: Large language models are increasingly deployed as course-specific tutors, but their usefulness depends on grounding in vetted instructional materials that are often revised mid-semester. Our prior work built a multimodal retrieval-augmented genera...
Source: arXiv - AI | 10 hours ago
Industry News
8. Five AI safety sessions every founder should have on their TechCrunch Disrupt 2026 agenda
At TechCrunch Disrupt 2026, five sessions across the AI Stage and Real World AI Stage cover AI safety, featuring leaders from Anthropic, Nvidia, AWS, Waabi, and more. Register before September 25 to save up to $200.
Source: TechCrunch - AI | 23 hours ago
About This Digest
This digest is automatically curated from leading AI and tech news sources, filtered for relevance to AI security and the ML ecosystem. Stories are scored and ranked based on their relevance to model security, supply chain safety, and the broader AI landscape.
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