Optimizing LLM Inference: Adaptive Cache Pollution Control with Temporal CNN and Priority-Aware Replacement
Published:Dec 16, 2025 07:16
•1 min read
•ArXiv
Analysis
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.
Key Takeaways
Reference
“The research focuses on cache pollution control.”