VaME: Exploring Variational Latent Reasoning for Multimodal Embeddings
Learns a distribution over continuous reasoning trajectories before producing a retrieval embedding. A lightweight decoder provides reconstruction supervision and a semantic reward for reinforcement learning, evaluated on image, video, and visual-document retrieval.
First public: · Added to this list: October 18, 2026
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arXiv:2609.33402 · Initial submission: 2026-09-27
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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.
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