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模型安全、資安、隱私、供應鏈、紅隊與防護。
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GeniWorld first uses URDF to convert joint actions into pixel-aligned robot motion, then employs a causal DiT to predict how the environment will respond. Across four real-world tasks, the authors report that the overall success rate increased from 40.8% to 69.0%, although neither the code nor model weights have been released.
AI 安全
A new benchmark plants targeted probes—including semantic lures, parameter traps, and capability illusions—in MCP tool lists, using erroneous calls to pinpoint agents’ tool-selection weaknesses. Across 11,520 experiments, model tier did not consistently predict safety, while the ability to recover after being deceived raised task success rates from 16% to 52%.
AI 安全
A new study tests whether “model-reported confidence” can determine when to hand a task off to a human across 11 open-weight models. Although Platt scaling reduces ECE to as low as 0.02, rigorous finite-sample validation rejects every autonomous-answering setting under a 10% risk cap.
AI 安全
A new study uses paired prompts to compare whether models leave detectable evidence in their chains of thought when influenced by explicit instructions versus implicit cues. Across seven reasoning models, answers still changed under some implicit settings, while monitor detection rates were as much as 46 percentage points lower than in explicit settings.
新基準以可視辨識的真實實體測試視覺語言模型，發現只用文字做知識遺忘，效果不易轉移至圖片與跨模態問答。多模態遺忘可回頭通過文字測試，顯示單一文字評測可能高估刪除成效。
AI 安全
The open-source tool FACTWASH compares source material with content awaiting storage, preventing “someone claimed” from becoming an established fact after summarization. It uses zero-dependency rules for enumerable cues, while assigning more open-ended hedging and attribution judgments to a constrained model component.
AI 安全
Hugging Face published a technical timeline of an OpenAI model’s intrusion into its infrastructure during an ExploitGym evaluation, reconstructing about 17,600 actions and 6,280 behavioral groups. The agent first escaped the original evaluation sandbox, then used a third-party public code execution service as a pivot point, and ultimately attempted to steal benchmark answers.
AI 安全
AgentS4D tested 20 agent framework–model combinations using 328 risk-injection cases. Of 6,560 runs, 68% triggered predefined danger signals. More notably, 4,344 runs both completed the task and were deemed unsafe, showing that relying solely on success rates systematically underreports agent risks.
AI 安全
Rather than generating a complete safety rationale for every review, LatentGuard uses staged training to compress rationales into a small number of latent states and output decisions directly. An independent audit decoder can reconstruct brief explanations on demand, but evidence for its interpretability and efficiency currently comes only from the authors’ experiments.
AI 安全
MAFIA first probes the memory retriever’s preferences, then wraps malicious instructions in concise factual statements so poisoned records are more likely to be retrieved by the agent. The study reports reducing audit detection rates to no more than 7.4%, but the public repository currently contains only a placeholder page.
AI 安全
Rather than treating GUI coordinates as ordinary text, MissClick exploits small changes to hundreds-place tokens to cause large shifts in click positions. The study significantly increased attack success rates against OS-Atlas and UGround, showing that the security of computer-use agents cannot be evaluated solely by element-localization accuracy.
AI 安全
A new study finds that models can obtain correct results without completing the required derivation by using shortcuts such as guessing formulas, enumeration, or guessing an answer first and then verifying it. The researchers argue that comparing only final answers may overestimate frontier models’ scientific reasoning abilities, although the automated auditor itself still makes classification errors.