An independent, evidence-graded read on how much you own the open models and inference providers you rely on.
A systems-security framework for evaluating trust in open-weight LLM deployments — air-gapped environments, hidden backdoors, and software supply chain integrity.
Solving the amnesiac problem for LLM agents. Research series on agents that compound knowledge across sessions — first measurement: +4.6 pp accuracy lift on Terminal-Bench 2.1 with an open-weight executor and a single failure-derived skill file.
Preregistered cross-lingual evidence-sufficiency probing in Qwen3 — 6 languages, 29,206 paired QA constructions, frozen English probes, and a sealed one-shot evaluation.
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