Linear Direction, Linear Subspace, Conceptor (soft ellipsoidal region), Intrinsic-dimension profile across depth, Generalized Helix, Anisotropy, Linear Separability

Functional Subspace, where language models can use vector algebra to solve problems (2026), Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models (2023), Summing Up the Facts: Additive Mechanisms Behind Factual Recall in LLMs (2024), Steering Large Language Models using Conceptors: Improving Addition-Based Activation Engineering (2024), Knowledge in Superposition: Unveiling the Failures of Lifelong Knowledge Editing for Large Language Models (2025), Function Vectors in Large Language Models (2024), In-Context Learning Creates Task Vectors (2023), Unifying Attention Heads and Task Vectors via Hidden State Geometry in In-Context Learning (2025), Do Different Prompting Methods Yield a Common Task Representation in Language Models? (2025), Memorization in Language Models through the Lens of Intrinsic Dimension (2025), Language Models Use Trigonometry to Do Addition (2025), Discovering Latent Knowledge in Language Models Without Supervision (2023), Linearity of Relation Decoding in Transformer Language Models (2023), Mass-Editing Memory in a Transformer (2022), Fast Model Editing at Scale (2022), Linearly Mapping from Image to Text Space (2023), Language Models Implement Simple Word2Vec-style Vector Arithmetic (2024), Probing then Editing Response Personality of Large Language Models (2025), Model Editing as a Robust and Denoised Variant of DPO: A Case Study on Toxicity (2024), The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models (2024), Identifying Linear Relational Concepts in Large Language Models (2023), Locating and Editing Factual Associations in GPT (2022), Large Language Models Encode Semantics and Alignment in Linearly Separable Representations (2025), Linear Relational Decoding of Morphology in Language Models (2025)