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LLM agents can now be monitored and intervened upon in real-time, saving 18% of compute by detecting failures within the first 8 steps with 83% accuracy.
Otap reveals that traditional evaluation methods fail to capture the nuances of agent planning, enabling a more robust distinction between valid and invalid trajectories.
Decentralized cell-level gating in Localized LoRA-MoE achieves performance parity with centralized routing while safeguarding against optimization deadlocks and gradient warfare.
