Optimizing LLM Inference: Adaptive Cache Pollution Control with Temporal CNN and Priority-Aware Replacement

This research addresses a critical performance bottleneck in Large Language Model (LLM) inference: cache pollution. The proposed method, leveraging Temporal CNNs and priority-aware replacement, offers a promising approach to improve inference efficiency.