SeMoCo: A Semantic-First Motion Codec for Motion Language Modeling

arXiv:2608.24334 · cs.CV, cs.CL, cs.GR · Submitted 2026-08-25 · Read on arXiv

cs.CV, cs.CL, cs.GR

Submitted: 2026-08-25

Updated: 2026-08-28

Code: https://github.com/OMEGA-i/SeMoCo-Tokenizer

Terminology

• Transformer — 18× in this paper · explained in 2 episodes
• Alignment — 12× in this paper · explained in 1 episode
• Ablation — 10× in this paper · explained in 1 episode
• Embeddings — 8× in this paper · explained in 2 episodes
• Provenance — 8× in this paper · explained in 3 episodes
• Quantization — 8× in this paper · explained in 12 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• Adaptation — 5× in this paper · explained in 1 episode
• Cosine Similarity — 5× in this paper · explained in 3 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Reconstruction Error — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Text-to-Motion Retrieval — 3× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Actor — 2× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Tokenization — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Human Motion Diffusion Model — 1× in this paper
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• AudioLM: a Language Modeling Approach to Audio Generation
• Executing your Commands via Motion Diffusion in Latent Space
• Simple and Controllable Music Generation
• High Fidelity Neural Audio Compression
• Qwen3-TTS Technical Report
• Pose-Guided Residual Refinement for Interpretable Text-to-Motion Generation and Editing
• MotionGPT: Human Motion as a Foreign Language
• VersatileMotion: A Unified Framework for Motion Synthesis and Comprehension
• Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation
• Kimodo: Scaling Controllable Human Motion Generation
• SOMA: Unifying Parametric Human Body Models
• Human Motion Diffusion Model
• Neural Discrete Representation Learning
• Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers
• MotionBricks: Scalable Real-Time Motions with Modular Latent Generative Model and Smart Primitives
• UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation
• HY-Motion 1.0: Scaling Flow Matching Models for Text-To-Motion Generation
• SoundStream: An End-to-End Neural Audio Codec
• SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

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