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University of Oxford

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Detecting Multi-Agent Collusion Through Multi-Agent Interpretability

QuestionCan activation-based group detectors generalize from known collusion to new scenarios?

Source summaryEvery model reached 1.00 in-distribution AUROC.

NUWA research note · independent review pending · Contains: question / method / findings / interpretation / limits

Quantifying Frontier LLM Capabilities for Container Sandbox Escape

QuestionCan agents escape intentionally weakened container sandboxes under controlled conditions?

Source summaryThe updated results report Opus 4.5 success on 56% of samples.

NUWA research note · independent review pending · Contains: question / method / interpretation / limits

CybersecurityCapability

Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples

QuestionDoes increasing clean-data scale dilute a fixed adversarial insertion enough to prevent a backdoor?

Source summaryComparable insertion counts can affect models trained on substantially different amounts of clean data.

NUWA research note · independent review pending

Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs

QuestionCan withholding domain knowledge at pretraining provide a more durable safeguard than post-training alone?

Source summaryFiltered models preserve measured unrelated capabilities while reducing the targeted proxy knowledge.

NUWA research note · independent review pending · Contains: question / method / findings / interpretation / limits

Risk GovernanceTechnical report

Model evaluation for extreme risks

QuestionHow should evaluation evidence constrain frontier development when tests cannot cover every risk?

Source summaryThe proposed workflow includes both pre-training assessment and ongoing evaluation during development.

NUWA research note · independent review pending

Cross-cutting research