Papers with graph-to-text translation
Colorful Talks with Graphs: Human-Interpretable Graph Encodings for Large Language Models (2026.findings-acl)
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| Challenge: | Graph problems require reasoning over explicit structure, permutation invariance, and computationally complex relationships, creating a mismatch with the representations of text-based models. |
| Approach: | They propose a human-interpretable structural encoding strategy that injects graph structure directly into natural language prompts. |
| Outcome: | The proposed method improves performance on synthetic and real-world datasets. |