Mapping Text to Multiplex Graph: Prompt Compression as Lévy Walk-Guided Graph Pruning
Existing prompt compression methods treat text as flat token sequences, failing to capture the distributed nature of important information, which is often spread across multiple locations and connected through both local syntactic dependencies and global semantic relations. Such relational structure is naturally represented as a graph, where tokens or sentences become nodes and their dependencies become edges. To this end, we propose RAGP, which formulates prompt compression as Redundancy-Aware Graph Pruning on a multiplex graph that jointly models fine-grained attention-based dependencies and coarse-grained semantic relations. To efficiently identify non-redundant nodes in this heterogen...
| Authors | Yaxin Gao, Yao Lu, Jinhong Deng et al. |
|---|---|
| Primary category | cs.CL |
| Published | 4 May 2026 |
| Last updated at source | 14 September 2026 |
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