SupraTok: Cross-Boundary Tokenization for Enhanced Language Model Performance

arXiv:2508.11857 · cs.CL, cs.AI, cs.LG · Submitted 2025-08-16 · Read on arXiv

cs.CL, cs.AI, cs.LG

Submitted: 2025-08-16

Updated: 2026-08-29

Terminology

• Tokenization — 48× in this paper · explained in 2 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Consistency — 4× in this paper · explained in 3 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Bayesian Optimization — 2× in this paper · explained in 3 episodes
• Byte-Pair Encoding — 2× in this paper
• Perplexity — 2× in this paper · explained in 3 episodes
• Scaling Laws — 2× in this paper · explained in 4 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Approximate Counting — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Edge Deployment — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Massive Multitask Language Understanding — 1× in this paper
• Objective Function — 1× in this paper · explained in 2 episodes
• Pointwise Mutual Information (PMI) — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Scaling Laws for Neural Language Models
• Training Compute-Optimal Large Language Models
• Sparks of Artificial General Intelligence: Early experiments with GPT-4
• Deep Learning Scaling is Predictable, Empirically
• The Pile: An 800GB Dataset of Diverse Text for Language Modeling
• Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
• Byte Latent Transformer: Patches Scale Better Than Tokens
• SuperBPE: Space Travel for Language Models
• Boundless Byte Pair Encoding: Breaking the Pre-tokenization Barrier

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