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Search: “Haiku 4.5”

3 stories in the last 7d

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CategoryAllAI research 1AI safety & security 1AI tools & infra 1
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Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents

Fine-tuned RoBERTa-large task permission classifier matches Claude Haiku 4.5 on access scoping for AI agents, cutting severity-weighted attack surface by 84.4%.

The paper evaluates a three-source task-based permission architecture for AI agents combining role-based permission ceilings, a task permission classifier, and policy-based prohibitions. A fine-tuned RoBERTa-large security gate matched few-shot Claude Haiku 4.5 on a 600-prompt dataset, with macro-F1 0.881 versus 0.886, precision 0.897 versus 0.842, and lower severity-weighted residual risk (0.63 versus 1.12). An attack-surface elimination metric shows the role ceiling alone closes 27.9% of the severity-weighted surface while adding the task classifier closes 84.4%. The work establishes task-granular access control as a measured, deployable mechanism for reducing attack surface in agentic deployments.

arXiv cs.CR · 2d agoAI safety & security

Show HN: How Stale Is Your AI? Release age and training cutoff for 20 models

A new site tracks release dates and training cutoffs for 20 AI models across 8 labs, exposing months-long staleness gaps.

A community-built page, launched via Show HN, tracks release dates and training cutoff dates for 20 current models from 8 labs including OpenAI, Anthropic, Google DeepMind, Meta, Mistral AI, Alibaba, DeepSeek, and xAI. Only 10 of the 20 models have lab-published cutoff dates, with data available as models.json. For example, GPT-6 Astra shipped September 3, 2026 with an April 30, 2026 cutoff. The page argues web search tools paper over, but never close, the staleness gap.

Hacker News · AIupdated · 3h agofirst · 21h agoAI tools & infra 13 sourcesHN 41↑ · 30 comments

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

Evaluation of twelve LLMs on 222 clinical questions shows verbatim quotes rarely substantiate claims; claude-opus-5 fully substantiates only 37.1%.

The authors build a standardized harness over four clinical practice guidelines and evaluate twelve LLMs on 222 synthetic clinical questions, measuring citation attachment, verbatim quote production, and claim substantiation. Most models attach verbatim quotes to over 90% of claims from prompting alone, though lightweight models like claude-haiku-4.5 struggle. Quotes frequently fail to substantiate claims: claude-opus-5 quotes 98.0% of claims but fully substantiates only 37.1%, exposing a capability gap for verifiable clinical QA.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research