Compressing conversational context without losing the thread
Metre-2 improved CoQA accuracy from 93.3% to 95.3% while cutting tokens by 8.2%.
Metre-2 improved CoQA accuracy from 93.3% to 95.3% while cutting tokens by 8.2%.
Cut safety classifier costs by 30% while preserving or improving F1.
Compressed prompts outperformed uncompressed in a 268K-vote blind arena across models.