Oddin: Latent Visual Reasoning in Unified Multimodal Models via Self-Distillation from Image Generation
Replaces intermediate generated images with learned latent-token blocks while retaining the written reasoning between them. Self-distills successful text-image traces into a unified multimodal model, reserving image generation for the final output.
First public: · Added to this list: November 2, 2026
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Thinking tokens — Give a model extra tokens for computation, such as pauses, filler symbols, or learned planning tokens. These tokens need not spell out the solution.
Continuous-state reasoning — Use vectors—lists of numbers—to carry intermediate reasoning from one step to the next, instead of selecting a text token at every step. Some methods use the model's hidden states; others combine several candidate token representations.