Researchers propose TSG to improve Text-to-Video timing in prompts
A new paper on arXiv introduces Temporal Specification Guidance (TSG), a method to better align text-to-video models with the timing and sequencing described in prompts. Current models often generate correct visuals but fail to match the intended order, duration, or persistence of actions or objects. TSG uses temporal logic to encode these requirements as formal specifications, then guides video…
Key points
- TSG uses temporal logic to enforce prompt timing and sequencing in text-to-video models
- Tests on 220 prompts improve accuracy by 9.5–20 percentage points over current methods
- No retraining or external classifiers needed; works via differentiable scoring and attention biases
The approach scores video frames using differentiable metrics tied to Metric Temporal Logic (MTL) and adjusts attention biases via gradients. Tests on 220 prompts across 11 categories—including object entry sequences and state transitions—show TSG improves accuracy by 9.5–20 percentage points over existing methods. The method avoids backpropagation through video transformers and requires no external classifiers, making it lightweight. The authors claim it could offer a flexible way to control temporal aspects of video generation.
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