specific method · filed under model architecture
Decoupled Encoder Process (DEP)
A process that separates ViT and text training into stages and balances vision passes across pipeline-parallel stages.
Also called decoupled encoder process.
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we introduced the Decoupled Encoder Process (DEP) [59], which splits ViT and text training into separate stages and balances vision forward and backward passes across PP stages.
usedsoftware implementationin Kimi K3Moonshot AI
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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 encodingDedicated multimodal encodersDisaggregated encoder trainingDiscarding the LLM after vision-encoder trainingDual-format coordinate supervisionExplicit text-string timestampsFour-frame audio patches with within-patch bidirectional self-attentionFrom-scratch vision-encoder training with next-token prediction