Unverified50% confidenceConceptExact time
The key difference between Jev-style decision models and conventional instruct/chat models lies in the training objective and output constraints.
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Long-term
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10/15/2026
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UnverifiedThe Jev team uses a new model architecture, a parallel sampler, and a training method called "Calibrated Decision Reinforcement Learning".74% similarUnverifiedFoundation models for agent tasks differ markedly in training objectives from models for general conversation; the former place more emphasis on tool calling, multi-step planning, error recovery and the ability to use environmental feedback, and their training data often contains a large number of stateful interaction trajectories.72% similarUnverifiedThe differences in how models respond to prompts mainly come from three levels: training data composition, architecture and context window, and coverage of the continued-training corpus.70% similarUnverified不同模型在抗诱导能力上的差异很大程度上源于后训练阶段（post-training）的策略差异70% similar
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