Compressing Long Context into Answer-Aligned Memory Embeddings for LLM Inference
arXiv:2609.25537v1 Announce Type: cross Abstract: Large language model (LLM) inference is constrained by the quadratic scaling of self-attention and the linear scaling of the KV cache, increasing latency, energy consumption, and GPU memory demand as context length scales. Existing soft-compression…