Brownian occupation measures conditioned on large self- or mutual-intersections converge weakly to the square of a Gagliardo-Nirenberg optimizer via new large deviation principles.
Improving image generation with better captions
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Auto-Rubric as Reward externalizes VLM preferences into structured rubrics and applies Rubric Policy Optimization to create more reliable binary rewards for multimodal generation, outperforming pairwise models on text-to-image and editing benchmarks.
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Asymptotics of Brownian occupation measures with unusually large intersections
Brownian occupation measures conditioned on large self- or mutual-intersections converge weakly to the square of a Gagliardo-Nirenberg optimizer via new large deviation principles.
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Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria
Auto-Rubric as Reward externalizes VLM preferences into structured rubrics and applies Rubric Policy Optimization to create more reliable binary rewards for multimodal generation, outperforming pairwise models on text-to-image and editing benchmarks.