implementation detail · filed under model architecture
Dual-format coordinate supervision
Coordinate supervision uses both absolute values and normalized values in the [0,1] range.
Also called coordinate supervision.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
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Evidence
1 span quoted from the sources, strongest treatment first.
coordinate supervision is provided in both absolute and normalized ([0,1]) formats, enabling precise and resolution-robust localization.
useddata curationin Kimi K3Moonshot AI
Filed alongside
Other methods under model architecture :: multimodal architecture.
Encoder-free multimodal architectureEarly fusion multimodal trainingDiscrete token encoding for audioHierarchical patch encoderMixed-modality trainingConfigurable visual token budgetJoint multimodal decoding in a shared hidden spaceNative multimodal understanding3×3 pixel-unshuffle downsamplingJoint vision-language pre-trainingRaw audio projection into the LLM embedding spaceVision Transformer (ViT)2×2 pixel-shuffle downsamplingAudio encoder initialized from MiMo-AudioAudio Transformer (AuT)Causal streaming ConvNet codec decoderData-parallel-first multimodal encodingDecoupled Encoder Process (DEP)Dedicated multimodal encodersDisaggregated encoder trainingDiscarding the LLM after vision-encoder trainingExplicit text-string timestampsFour-frame audio patches with within-patch bidirectional self-attentionFrom-scratch vision-encoder training with next-token prediction