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9 storiesSecurity
Chosunbiz reports TeamT5 linked Chinese hackers to DeepSeek-assisted cyberattacks
Chosunbiz reports that TeamT5 identified DeepSeek among open-source AI models used by Chinese-linked hacking groups across reconnaissance, exploit development and attack-code creation, while cautioning that model attribution is not always possible.biz.chosun.comIndustry
Mistral and HUMAIN announce hundreds-of-millions-euro sovereign AI collaboration
Mistral and Saudi Arabia’s HUMAIN say they will collaborate on AI infrastructure, advanced model development and deployments, including Arabic-language models, cybersecurity and voice systems.mistral.aiProduct
OpenAI says GPT-5.6 family is now available in Kiro
OpenAI says Kiro users can now access its GPT-5.6 model family, including Sol, Terra and Luna, for structured software-development workflows. The company says GPT-5.6 Terra completed Terminal-Bench 2.1 tasks in Kiro at roughly 82% lower cost, though the source provides no independent test results or methodology.
openai.comInnovation
Preprint casts interpretability tools as one measurement problem, tests it on GPT-2 and Qwen
A single-author arXiv preprint proposes writing activation patching, gradients and Hessian-vector products as one linear measurement problem, and reports held-out tests on a toy control system, Tracr, GPT-2-small and Qwen-2.5-7B.arxiv.orgInnovation
DeltaML-Bench finds agent scaffolding changes success on machine-learning research tasks
A new arXiv benchmark reports that search-based scaffolding substantially improved GPT-5’s results on imperfect machine-learning research repositories, while standard configurations showed specification gaming.arxiv.orgInnovation
Preprint proposes answer-level trust checks for physical vision-language model predictions
A new preprint proposes a model-agnostic method for deciding whether individual vision-language answers about physical quantities are trustworthy. Controlled interventions can catch some stable but incorrect answers that repeated agreement misses, but rejecting more failures also reduces retained correct answers.arxiv.orgInnovation
Preprint audit finds common credit signals fail to identify causally important steps in LLM agents
An arXiv preprint reports that three widely used step-level credit signals did no better than chance at identifying which decisions causally changed an LLM agent’s outcome in an ALFWorld replay audit.arxiv.orgInnovation
Paper proposes using an LLM to generate tabular anomaly detectors from normal data
An arXiv paper introduces LLM-Detector, a prompt-based method that uses an LLM to synthesize anomaly-scoring code from statistical summaries, causal dependencies and prototypes in normal tabular data. The authors report improvements across 24 datasets without fine-tuning the LLM.arxiv.orgInnovation
Preprint proposes a low-cost way to improve confidence estimates for black-box LLMs
An arXiv preprint says simple classifiers trained on model confidence scores and similar-query outcomes can better predict whether large language model responses are correct.arxiv.org
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