mlsanityData to 14 Oct 2026

Cell-Based Representation of Relational Binding in Language Models

arXiv 2604.19052 ↗First posted 21 Apr 2026cs.CLcited by 5

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Abstract (arXiv)

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 from attribute-token activations with Partial Least Squares regression. Across domains and two model families, the indices are linearly decodable and form a grid-like geometry in the projected space. We further find that context-specific CBR representations are related by translation vectors in activation space, enabling cross-context transfer. Finally, activation patching shows that manipulating this subspace systematically changes relational predictions and that perturbing it disrupts performance, providing causal evidence that LLMs rely on CBR for relational binding.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 19 of its 48 references that are in the map. First posted on arXiv 21 Apr 2026.

Builds on

19 of 48 references.

References · 19

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2025Qwen3 Technical Reportcited by 8,820
  3. 2022Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 smallcited by 1,165
  4. 2022Toy Models of Superpositioncited by 971
  5. 2022In-context Learning and Induction Headscited by 964
  6. 2023The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasetscited by 712
  7. 2022Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Taskcited by 431
  8. 2023Language Models Represent Space and Timecited by 316
  9. 2023Linearity of Relation Decoding in Transformer Language Modelscited by 200
  10. 2023Linear Representations of Sentiment in Large Language Modelscited by 163
  11. 2024Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Trackingcited by 149
  12. 2024The Remarkable Robustness of LLMs: Stages of Inference?cited by 146
7 more
  1. 2023How do Language Models Bind Entities in Context?cited by 108
  2. 2024Monitoring Latent World States in Language Models with Propositional Probescited by 43
  3. 2024Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distributioncited by 27
  4. 2025Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Contextcited by 26
  5. 2025Large Language Models Encode Semantics and Alignment in Linearly Separable Representationscited by 17
  6. 2025Probing Latent Subspaces in LLM for AI Security: Identifying and Manipulating Adversarial Statescited by 9
  7. 2025Linear Spatial World Models Emerge in Large Language Modelscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

  1. 2026Relational Rank Geometry in Transformers: Detecting and Steering Hidden-State Relation Framescited by 0
  2. 2026How Do Language Models Choose Between Context and Memory?cited by 0
  3. 2026A Circuit for Plural Reference: How LLMs Represent and Retrieve Singular and Plural Entitiescited by 0
  4. 2026Causal and Interpretable Structures in LLM Compositional Taskscited by 0
  5. 2026The Geometry of Contextual Relations: Language Models Address Facts by Order of Mentioncited by 0

Similar, not cited

Close in wording, no citation either way

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  2. 2025WUGNECTIVES: Novel Entity Inferences of Language Models from Discourse Connectives
  3. 2026Linear Representations of Hierarchical Concepts in Language Models
  4. 2025SR-LLM: Rethinking the Structured Representation in Large Language Model
  5. 2026Do Language Models Encode Semantic Relations? Probing and Sparse Feature Analysis
  6. 2025Can an LLM Induce a Graph? Investigating Memory Drift and Context Length
  7. 2026Entity Binding Failures in Speech LLM Reasoning: Diagnosis and Chain-of-Thought Intervention
  8. 2025BeDiscovER: The Benchmark of Discourse Understanding in the Era of Reasoning Language Models