If it is a counter (e.g.

To achieve this goal, we provide a generative diffusion-based framework called MomentDiff, which simulates a typical human retrieval process from random browsing to gradual localization. Specifically, we first diffuse the real span to random noise, and learn to denoise the random noise to the original span with the guidance of similarity between text and video.

Proposition 2.5 is a direct consequence of the following lemma (remember that Lemma A.1 (Smooth functions conserved through a given flow.) . Assume that @h () ()=0 for all 2 . Let us first show the direct inclusion. Now let us show the converse inclusion. We recall (cf Example 2.10 and Example 2.11) that linear and Assumption 2.9, which we recall reads as: Theorem 2.14, let us show that (9) holds for standard ML losses.