Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

arXiv:2509.22161 · cs.LG, cs.AI · Submitted 2025-09-26 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-09-26

Updated: 2026-09-27

Terminology

• Quantization — 68× in this paper · explained in 12 episodes
• Regularization — 31× in this paper · explained in 3 episodes
• Perplexity — 15× in this paper · explained in 3 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 6× in this paper
• Transformer — 5× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Frechet Inception Distance — 3× in this paper
• Representation Learning — 3× in this paper · explained in 2 episodes
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Self-Supervised Learning — 2× in this paper · explained in 8 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Kullback-Leibler (KL) Divergence — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Predictive Coding — 1× in this paper · explained in 2 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

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