Unverified50% confidenceFactExact time
CoPE maintains the conventional one-step-at-a-time action approach during inference, produces no additional computational overhead, and requires no additional models, separate pre-training, or ensemble inference.
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10/15/2026
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UnverifiedDuring the inference phase, only forward propagation needs to be executed; gradient computation and backpropagation are not required.69% similarUnverifiedThe core mechanism of CoPE is that, on successful on-policy trajectories, it simultaneously supervises the policy backbone to generate subsequent multi-step action sequences and each action to be individually predicted from its preceding history.68% similarVerifiedEach inference call to a large model is an independent forward pass; the model weights are completely fixed during inference and there is no mechanism to preserve state across conversation sessions.66% similarUnverifiedLLM采用无状态设计，模型权重在训练后被固化，推理时不会因某次对话而改变内部参数66% similarUnverifiedModel selection should not rely solely on overall benchmark scores, but should be comprehensively evaluated in conjunction with stability performance in specific application scenarios.65% similar
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