n0n extortion operator exposed AI-aided attack files on open server
SOCRadar says every examined break-in used weak or stolen credentials, not a software vulnerability.
SOCRadar says every examined break-in used weak or stolen credentials, not a software vulnerability.
Across 14 models, post-training and verifiable-reward training pushed text further from human writing than base models.
Guidance covers 30 risk types, unsigned model files, and backdoors that behavioral tests may miss.
Researchers showed open-weight models can hide backdoors that pass evals and exfiltrate credentials when a trigger appears.
Across 32 LLMs, newer models are safer in absolute terms, but no family closes the code security gap.
Airbnb’s CTO says about 60% of code is AI-authored and AI resolves roughly half of support tickets.
Language-model self-repair is explained as pre-existing counterweights following an affine response to ablation dose.
DuoOPD uses joint teacher-student outcomes to improve multi-task on-policy distillation over standard OPD.
OpenRouter’s CEO discusses its Stripe deal, multi-model routing, and rising agentic token fraud.
Meta's Muse agent now gives each user a free Ubuntu cloud computer isolated by a Sentinel monitor.
A reverse-auction procurement platform learns LLM quality and price, finding 10–71% margins across Llama and Qwen tasks.
Survey finds LLM mobility research largely neglects security, privacy, and EU AI Act compliance despite transportation AI's high-risk classification.
A report finds Chinese open-weight AI models now outperform American counterparts in downloads and benchmarks.
PIR reads internal states to separate concealed model knowledge from genuine ignorance across eight language models.
Researchers show EOS termination-token mismatch between base students and post-trained teachers drives length inflation in on-policy distillation across Qwen3, Llama, and Gemma.
Researchers propose ComPO, a zeroth-order comparison-based preference alignment method with convergence guarantees that mitigates likelihood displacement in LLMs.
ComPO is a zeroth-order preference alignment method using comparison oracles to mitigate likelihood displacement across Mistral, Llama, Gemma, and Qwen3 models.
Interconnects publishes a curated open-model reading list covering release strategy, US-China competition, adoption data, and a narrowed 4-6 month open-closed frontier gap.
Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.
NTNU and Aegean researchers open-source a software-emulated Wi-Fi cyber range using mac80211_hwsim with LLM-assisted scenario building.
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