"LatentPress: Context Compression Beyond Text and Vision" by Zhengze Zhou , Hejian Sang
TLDR:
LatentPress is a new approach that compresses conversational and document context into continuous memory tokens, which are read directly by a frozen decoder. This method achieves high compression rates, faster inference times, and improved accuracy compared to traditional text or OCR methods. LatentPress uses a small reader-matched writer to compress context while training only an adapter, achieving impressive results on evaluation tasks like LongMemEval and LongBench-QA. The implementation of this approach is significantly faster than text summarization or OCR reconstruction, making it a practical and efficient method for processing contextual information in machine-facing interfaces.
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Paper page - LatentPress: Context Compression Beyond Text and Vision
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1September 4, 2026 48
