Latent Motion Reasoning for Text-to-Motion Generation
Published:Dec 30, 2025 09:17
•1 min read
•ArXiv
Analysis
This paper addresses the Semantic-Kinematic Impedance Mismatch in Text-to-Motion (T2M) generation. It proposes a two-stage approach, Latent Motion Reasoning (LMR), inspired by hierarchical motor control, to improve semantic alignment and physical plausibility. The core idea is to separate motion planning (reasoning) from motion execution (acting) using a dual-granularity tokenizer.
Key Takeaways
Reference
“The paper argues that the optimal substrate for motion planning is not natural language, but a learned, motion-aligned concept space.”