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AgentDoG 1.5 proves you can achieve GPT-5.4-level agent safety with open-source models trained on just 1k samples, slashing deployment overhead by two orders of magnitude.
AgentSchool offers a powerful new way to simulate educational environments, moving beyond simple role-play to model learning as a dynamic state transition and providing a testbed for long-horizon memory and multi-agent coordination.
Even minor real-world environment corruptions can cripple MLLM-powered computer-use agents, revealing a surprising fragility in their ability to execute desktop tasks.
LLM-based multi-agent systems are riddled with 20 distinct risk types, from single-agent vulnerabilities to system-level emergent hazards, demanding a unified safety evaluation and monitoring framework.
