Mmm.txt -

: You can view the full paper on arXiv:2312.03596 .

: Visual examples of the generated motions can be found on their Project Page . ❓ Other Possible Interpretations

: The masked modeling approach naturally allows for motion in-filling and editing. 🛠️ Resources & Implementation mmm.txt

: Transforms complex 3D human motion into a sequence of discrete tokens in a latent space.

: A benchmark for evaluating Large Language Models on long documents (up to hundreds of pages). : You can view the full paper on arXiv:2312

Knowing the subject (e.g., human motion, document AI, or satellite imagery) will help me provide a more specific summary.

: Explicitly captures dependencies among tokens and semantic mapping between text and motion. 🌟 Key Advantages 🛠️ Resources & Implementation : Transforms complex 3D

: Learns to predict randomly masked motion tokens based on pre-computed text tokens.