Large language models encode relational bindings via a cell-based representation: a low-dimensional linear subspace in which each cell corresponds to an entity-relation index pair and attributes are retrieved from the matching cell.
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cs.CL 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
Scene Abstraction framework builds structured scene representations for lexical meaning via LLM prompting, with COCA-Scenes dataset and human experiments showing 82.4% identification accuracy and 86.4% preference over ATOMIC baselines.
LLMs perform in-context learning as trajectories through a structured low-dimensional conceptual belief space, with the structure visible in both behavior and internal representations and causally manipulable via interventions.
citing papers explorer
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Cell-Based Representation of Relational Binding in Language Models
Large language models encode relational bindings via a cell-based representation: a low-dimensional linear subspace in which each cell corresponds to an entity-relation index pair and attributes are retrieved from the matching cell.
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Scene Abstraction for Lexical Semantics: Structured Representations of Situated Meaning
Scene Abstraction framework builds structured scene representations for lexical meaning via LLM prompting, with COCA-Scenes dataset and human experiments showing 82.4% identification accuracy and 86.4% preference over ATOMIC baselines.
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Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space
LLMs perform in-context learning as trajectories through a structured low-dimensional conceptual belief space, with the structure visible in both behavior and internal representations and causally manipulable via interventions.