Concept rather than Document: Context Compression via AMR-based Conceptual Entropy (2026.findings-acl)
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| Challenge: | Existing methods rely on lexical or token-level features that fragment semantic units and fail to capture conceptually essential content. |
| Approach: | They propose an unsupervised framework leveraging Abstract Meaning Representation to preserve essential information while filtering irrelevant text. |
| Outcome: | The proposed framework outperforms RAG and existing baselines while preserving essential information while filtering irrelevant text. |
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