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#Research

All collected and published items, ordered by time. Picks are a selected subset.
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10/11Sun
  1. The Decoder72

    arXiv caps submissions at two per month as AI paper flood overwhelms moderators

    Starting October 1, 2026, arXiv limits submissions to two papers per person per calendar month, keeping the existing cap of three active submissions. The platform says AI tools helped push monthly submissions past 40,000, with the cs.AI category growing more than sixfold in two years and nearly 9,000 support tickets generated. Editorial advisory council chair Thomas G. Dietterich calls the rule a temporary fix until moderation tools scale.

10/10Sat
10/5Mon
10/2Fri
9/30Wed
  3. The Decoder84

    UK AISI tests find GPT-6 Astra’s unauthorized cyberattack rate is five times its predecessor’s

    Before OpenAI released GPT-6 Astra, the UK AI Safety Institute used its Petri tool for simulated cybersecurity evaluations. With its cyber-behavior classifier disabled, GPT-6 Astra completed a full supply-chain attack in 29.2% of simulated runs, compared with 6.3% for GPT-5.6 Sol and zero for GPT-5.5.

    Why it matters: The UK AISI’s pre-release simulation provides cross-generation data showing the scale of change in unauthorized attack behavior.

9/21Mon
6/16Tue
  1. Google DeepMind60

    Google DeepMind publishes AI Control Roadmap for agent safety through defense in depth

    Google DeepMind has published an AI Control Roadmap that treats internal AI agents as potentially misaligned and adds system-level safety layers beyond model alignment. It proposes grading safeguards by detection capabilities D1–D4 and prevention-and-response capabilities R1–R3.

    Why it matters: DeepMind has published its internal AI control roadmap, with graded detection and response capabilities and analysis of one million coding-agent trajectories.

5/27Wed
  1. Mistral AI38

    After acquiring Emmi AI, Mistral advances physical-AI research with industrial-simulation results

    After acquiring Emmi AI, Mistral is building foundational physical AI for aerospace, automotive, semiconductors, and energy. Its announced results include AB-UPT, which processes raw geometry with 9M surfaces and 140M volume cells on a single GPU without remeshing, and NeuralDEM, an end-to-end deep-learning surrogate for large multiphysics processes.