Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes [R]

Excerpt

coupled-jump.github.io Hi everyone, I’m happy to share our recent NeurIPS 2026 paper, a collaboration across Google, Google DeepMind and Stony Brook University. We study a mismatch in joint text and image generation: a model can describe the correct solution to a maze while drawing a different path. Generating both outputs in parallel doesn’t necessarily keep them consistent. Our sampler, CO₂Jump, uses text confidence and cross-modal attention to guide image updates during sampling. It also allo