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PASTABench: Proactive Assessment of Sequential Trajectories for Agent Safety

As Large Language Models (LLMs) evolve into autonomous agents that alter real-world states, ensuring operational safety across multi-step workflows has become a critical challenge. While recent work has moved beyond single-turn evaluation toward multi-turn paradigms, key limitations persist: step-level methods treat actions in isolation, missing how risks accumulate, while trajectory-level…

We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.

Read the original at arxiv.org →

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How Jev Works: The Logit Trick Behind TypeSafe's System One Model

For the last few weeks my timeline has been nothing but Jev. TypeSafe AI shipped it, and within days there was an awesome-jev list, a jev-mcp server, a LangChain integration, and about ten thousand…

  • Jev is a closed, fast classification model running on TypeSafe's servers
  • Logit trick converts model's prefill scores into single token responses
  • Jev provides fast, accurate, limited responses without free text

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