WRSWorld Research StateContribute
WORLD RESEARCH STATE

LLMLingua: budgeted coarse-to-fine prompt compression

Contribution grade

Prompt compression · Human-designed research method or resource

Reference score80,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Combined a prompt-component budget controller, iterative token compression and small-model distribution alignment to compress inputs for an otherwise black-box language model.

Scientific scope

Combined a prompt-component budget controller, iterative token compression and small-model distribution alignment to compress inputs for an otherwise black-box language model. Inherits selective-context/self-information compression. Removing low-perplexity tokens does not guarantee preserved meaning or answers on arbitrary inputs. Compression-model tuning/compute costs remain and historical API price savings are not current prices.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits selective-context/self-information compression. Removing low-perplexity tokens does not guarantee preserved meaning or answers on arbitrary inputs. Compression-model tuning/compute costs remain and historical API price savings are not current prices.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

Full scientific record · Browse contribution grades · Request a correction