Short Horizons and Sparse Concepts: a Mathematical View of the Readout in the J-lens

arXiv:2608.25347 · cs.CL · Submitted 2026-08-26 · Read on arXiv

cs.CL

Submitted: 2026-08-26

Updated: 2026-08-26

Terminology

• Decoupling — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Non-Gaussianity — 2× in this paper · explained in 2 episodes
• Score Function — 2× in this paper · explained in 4 episodes
• Systematic Bias — 2× in this paper · explained in 3 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Eliciting Latent Predictions from Transformers with the Tuned Lens
• Verbalizable Representations Form a Global Workspace in Language Models
• In-context Learning and Induction Heads
• Qwen3 Technical Report

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