Kathleen Writes: Autoregressive Generation and Data Scaling Without Attention

arXiv:2608.04678 · cs.CL, cs.LG · Submitted 2026-08-05 · Read on arXiv

George Fountzoulas

cs.CL, cs.LG

Submitted: 2026-08-05

Comments: Paper 3 of the Kathleen series. 11 pages, 3 figures. All experiments reproducible on a free Kaggle T4

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 12× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Decode — 4× in this paper · explained in 2 episodes
• Perplexity — 4× in this paper · explained in 3 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Provenance — 3× in this paper · explained in 4 episodes
• Frozen model — 2× in this paper · explained in 3 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Affective Computing — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Scaling Laws for Neural Language Models
• Kathleen: Oscillator-Based Byte-Level Text Classification Without Tokenization or Attention

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