AI BriefingNative Multimodal Modeling (GitHub Repository)
Key point
Provides a roadmap and model list for Native Multimodal Modeling (NMM), which goes beyond modular combination to jointly process multiple modalities.
Details
Existing multimodal approaches have mainly relied on Modular Assembly, combining different modules, but this had fundamental limitations in processing raw sensor signals.
Recently, the paradigm has been shifting toward Native Multimodal Modeling (NMM), which directly integrates multiple modalities into a Unified Transformer Space or Joint Backbone.
This repository systematically organizes the NMM ecosystem by classifying it according to integration depth and input/output structure, as follows:
- M2T (Multi-to-Text): Performs reasoning by converting multimodal inputs into text
- M2G (Multi-to-Target): Directly synthesizes a specific modality to ensure temporal and acoustic consistency
- M2M (Multi-to-Multi): A unified paradigm that performs understanding and generation simultaneously
It also presents a technical roadmap through the related paper "Toward Native Multimodal Modeling: A Roadmap," helping readers track the latest landmark models.
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