arXiv cs.CLPaper
FlexComp: One Model for Every Ratio in Context Compression
Context compression just became more practical. Existing compressors require separate models for each ratio and apply uniform compression regardless of input complexity, both wasteful. FlexComp trains once and compresses flexibly, with routing that preserves 98% accuracy at extreme compression. This is infrastructure that RAG and agent builders should test immediately—it removes a deployment friction point.