Cell-Based Representation of Relational Binding in Language Models
Understanding a discourse requires tracking entities and the relations that hold between them. While Large Language Models (LLMs) perform well on relational reasoning, the mechanism by which they bind entities, relations, and attributes remains unclear. We study discourse-level relational binding and show that LLMs encode it via a Cell-based Binding Representation (CBR): a low-dimensional linear subspace in which each ``cell'' corresponds to an entity--relation index pair, and bound attributes are retrieved from the corresponding cell during inference. Using controlled multi-sentence data annotated with entity and relation indices, we identify the CBR subspace by decoding these indices fr...
| Authors | Qin Dai, Benjamin Heinzerling, Kentaro Inui |
|---|---|
| Primary category | cs.CL |
| Published | 21 April 2026 |
| Last updated at source | 21 April 2026 |
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