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Real-time interactive world models typically need to adopt streaming inference schemes based on autoregressive or diffusion models, combined with state compression (such as encoding historical frames into compact latent representations) to reduce computational burden.
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10/27/2026
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Unverified通过向前向传播激活中添加或减去特定方向向量,可以实时调节模型在该概念维度上的表现,无需修改权重参数79% similarUnverifiedExisting context compression approaches typically have the model itself perform the compression process, causing the timing, granularity, and information trade-offs of compression to depend on the model's real-time judgment, which both consumes inference resources and is difficult to audit.76% similarUnverifiedModel quantization, knowledge distillation, and speculative decoding are the three mainstream model compression paths used to run multimodal models in real time on mobile devices.75% similarUnverifiedOn-the-fly adjustment means that the model dynamically updates its own parameters or tracking state based on real-time input during the inference stage, using historical frame information to maintain continuous state estimation and form temporal consistency.74% similarUnverifiedAn autoregressive world model refers to a generative model that takes the current or historical state as input and predicts future states step by step, commonly treating the scene representation at each moment as a token sequence and performing inference in temporal order with structures such as Transformers.73% similar
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