Corrupt Plans, Clean Traces: Evading Chain-of-Thought Monitoring with Plan Injection
Chain-of-thought (CoT) monitoring is a safety strategy where the reasoning of a large language model "actor" is inspe...
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Chain-of-thought (CoT) monitoring is a safety strategy where the reasoning of a large language model "actor" is inspe...
Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning throu...
We present Vidu S2, which comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Edit...
Training prompts in online reinforcement learning (RL) differ substantially in how informative they are for the curre...
We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting...
In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, syste...
Native 3D generators turn one image into a single mesh. TRELLIS.2 and its peers deliver high-fidelity non-watertight ...
As AI agents become participants in the development of their successors, they reshape both the production of intellig...
Large language model (LLM) agents allocate test-time compute adaptively as they revise solutions, use tools, explore ...
Vibe design agents turn natural-language briefs into rendered interfaces and frontend code. Yet a useful design agent...
Backdoor poisoning attacks add poisoned examples to otherwise-clean finetuning data, pairing a trigger with a target ...
We demonstrate that a general-purpose agent can directly drive a physical robot throughout task execution without any...