Linear Subspace, Linear Direction, Dimensional collapse, Anisotropy, Concept Crystals (Parallelogram/Trapezoid Structure), Intrinsic-dimension profile across depth, Platonic Representation Hypothesis, Relation-decoding operator (affine map between representation spaces), Representational-similarity trajectory across depth, Linear Separability, Continuous causal attention operator (CCT), Cumulant-expansion profile of the next-token softmax entropy

The Communication Map of a Transformer (2026), Steering Language Models With Activation Engineering (2024), Dimensional Collapse in Transformer Attention Outputs: A Challenge for Sparse Dictionary Learning (2025), BatchTopK Sparse Autoencoders (2024), Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models (2023), The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models (2026), On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders (2026), Analogies minus analogy test: measuring regularities in word embeddings (2020), Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space (2022), Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability (2026), Representational Curvature Modulates Behavioral Uncertainty in Large Language Models (2026), Language models align with brain regions that represent concepts across modalities (2025), Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility (2025), Linearity of Relation Decoding in Transformer Language Models (2023), Latent Semantic Manifolds in Large Language Models (2026), Invariant Reasoning Directions in Latent Trajectories of Language Models (2026), Language Models Implement Simple Word2Vec-style Vector Arithmetic (2024), Talking Heads: Understanding Inter-layer Communication in Transformer Language Models (2024), The Representational Geometry of Number (2026), Trajectory Geometry of Transformer Representations Across Layers (2026), Spectral Probe-Circuits: A Three-Step Recipe for Identifying Attention-Head Circuits in Pretrained Transformers (2026), Mapping Language Models to Grounded Conceptual Spaces (2022), Cognitive Maps in Language Models: A Mechanistic Analysis of Spatial Planning (2025), Outlier Dimensions Encode Task-Specific Knowledge (2023), Token Embeddings Violate the Manifold Hypothesis (2025), Locating and Editing Factual Associations in GPT (2022), Linear Representations of Sentiment in Large Language Models (2023), Language Models Are Implicitly Continuous (2025), The Blessing and Curse of Dimensionality in Safety Alignment (2025), Lines of Thought in Large Language Models (2024), Large Language Models Encode Semantics and Alignment in Linearly Separable Representations (2025), Scaling and Evaluating Sparse Autoencoders (2024), Transcoders Find Interpretable LLM Feature Circuits (2024), Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning (2025), Probing Geometry of Next-Token Prediction Using Cumulant Expansion of the Softmax Entropy (2025), Revisiting the Othello World Model Hypothesis (2025), Geometry of Semantics in Next-Token Prediction: How Optimization Implicitly Organizes Linguistic Representations (2025)