Omni-C: Compressing Heterogeneous Modalities into a Single Dense Encoder

ArXi:2603.05528v1 Announce Type: cross Recent multimodal systems often rely on separate expert modality encoders which cause linearly scaling complexity and computational overhead with added modalities. While unified Omni-models address this via Mixture-of-Expert (MoE) architectures with specialized experts and routing, they still inflate parameter counts and