MyoMechanix: Biomechanically-Grounded Compositional Skilled Activity Understanding and Coaching

arXiv:2608.26094 · cs.CV, cs.AI, cs.ET, cs.HC, cs.LG · Submitted 2026-08-26 · Read on arXiv

cs.CV, cs.AI, cs.ET, cs.HC, cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Terminology

• Action Quality Assessment — 44× in this paper
• Benchmark — 44× in this paper · explained in 2 episodes
• Core — 23× in this paper · explained in 2 episodes
• Alignment — 17× in this paper · explained in 1 episode
• Knowledge Graph — 17× in this paper · explained in 7 episodes
• Fitness Knowledge Graph — 16× in this paper
• Generalization — 15× in this paper · explained in 13 episodes
• Interpretability — 14× in this paper · explained in 15 episodes
• Ontology — 13× in this paper · explained in 2 episodes
• Fine-Tuning — 7× in this paper · explained in 5 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Verification — 7× in this paper · explained in 2 episodes
• Adaptation — 6× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Distribution Shift — 6× in this paper · explained in 5 episodes
• Multimodal Fusion — 6× in this paper · explained in 3 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Fidelity — 5× in this paper · explained in 2 episodes
• Representation Learning — 5× in this paper · explained in 2 episodes
• Structured Reasoning — 5× in this paper · explained in 3 episodes
• Grounding — 4× in this paper · explained in 3 episodes
• Actionability — 3× in this paper · explained in 3 episodes
• Activation Function — 3× in this paper · explained in 1 episode
• Aggregation — 3× in this paper · explained in 1 episode
• Foundation Model — 3× in this paper · explained in 3 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Multimodal Reasoning — 3× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accountability — 2× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• Causal Reasoning — 2× in this paper · explained in 2 episodes
• Cross-Attention Mechanism — 2× in this paper · explained in 2 episodes
• Flesch Reading Ease — 2× in this paper
• Graph Construction — 2× in this paper · explained in 3 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Mean Absolute Error — 2× in this paper
• Multimodal Inputs — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Root Mean Square Error — 2× in this paper
• Temporal Reasoning — 2× in this paper · explained in 2 episodes
• Type-Token Ratio — 2× in this paper
• Verifiability — 2× in this paper · explained in 2 episodes
• 3D Positional Encoding — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Annotation Errors — 1× in this paper · explained in 1 episode
• Causal Inference — 1× in this paper · explained in 4 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Error Localization — 1× in this paper · explained in 2 episodes
• Error Taxonomy — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Federated Learning — 1× in this paper · explained in 14 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Homogenization — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Mixture-of-Experts (MoE) — 1× in this paper · explained in 7 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Supervised Learning — 1× in this paper · explained in 7 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Spatio-temporal grounding — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• FitAQA: A Benchmark of Fitness Action Quality Assessment for Multimodal Large Language Models
• Learning to Visually Connect Actions and their Effects
• Uncertainty-Driven Action Quality Assessment
• SkillSight: Efficient First-Person Skill Assessment with Gaze
• Video Action Differencing
• RICA2: Rubric-Informed, Calibrated Assessment of Actions
• TVQA+: Spatio-Temporal Grounding for Video Question Answering
• Explainable Action Form Assessment by Exploiting Multimodal Chain-of-Thoughts Reasoning
• MiniCPM-V: A GPT-4V Level MLLM on Your Phone
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
• Qwen2.5-VL Technical Report
• LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

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