An adaptive delta-prioritization algorithm using cosine distance and Hamming-drift thresholds improves embedding distortion by 4.8-7.2% and next-token perplexity by 2.1-6.3% over periodic keyframing at matched low bitrates for tokenized driving world models.
and Ohm, Jens-Rainer and Han, Woo-Jin and Wiegand, Thomas , urldate =
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A neural network predicts optimal frame rate and resolution pairs for bandwidth-constrained streaming of rendered content to boost perceptual quality.
Sema reduces uplink bandwidth by 64x for audio and 130-210x for screenshots while keeping multimodal agent task accuracy within 0.7 percentage points of raw baselines in WAN simulations.
citing papers explorer
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Network-Efficient World Model Token Streaming
An adaptive delta-prioritization algorithm using cosine distance and Hamming-drift thresholds improves embedding distortion by 4.8-7.2% and next-token perplexity by 2.1-6.3% over periodic keyframing at matched low bitrates for tokenized driving world models.
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Streaming of rendered content with adaptive frame rate and resolution
A neural network predicts optimal frame rate and resolution pairs for bandwidth-constrained streaming of rendered content to boost perceptual quality.
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Sema: Semantic Transport for Real-Time Multimodal Agents
Sema reduces uplink bandwidth by 64x for audio and 130-210x for screenshots while keeping multimodal agent task accuracy within 0.7 percentage points of raw baselines in WAN simulations.