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@@ -164,6 +164,7 @@ Awesome-LLM-Inference: A curated list of [📙Awesome LLM Inference Papers with
 |2023.10|🔥[**Adaptive KV Cache Compress**] MODEL TELLS YOU WHAT TO DISCARD: ADAPTIVE KV CACHE COMPRESSION FOR LLMS(@illinois.edu&microsoft)|[[pdf]](https://arxiv.org/pdf/2310.01801.pdf)|⚠️|⭐️⭐️ |  
 |2023.10|[CacheGen] CacheGen: Fast Context Loading for Language Model Applications(@Chicago University&Microsoft)|[[pdf]](https://arxiv.org/pdf/2310.07240.pdf)|⚠️|⭐️ |  
 |2023.12|[KV-Cache Optimizations] Leveraging Speculative Sampling and KV-Cache Optimizations Together for Generative AI using OpenVINO(@Haim Barad etc) | [[pdf]](https://arxiv.org/pdf/2311.04951.pdf)|⚠️|⭐️ |    
+|2023.12|[KV Cache Compress with LoRA] Compressed Context Memory for Online Language Model Interaction (@SNU & NAVER AI) | [[pdf]](https://arxiv.org/pdf/2312.03414.pdf)|[[Compressed-Context-Memory]](https://github.com/snu-mllab/Context-Memory) ![](https://img.shields.io/github/stars/snu-mllab/Context-Memory.svg?style=social) |⭐️⭐️ |    
 |2024.01|🔥🔥[**DistKV-LLM**] Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache(@Alibaba etc)|[[pdf]](https://arxiv.org/pdf/2401.02669.pdf)|⚠️|⭐️⭐️ |
 |2024.02|🔥🔥[Prompt Caching] Efficient Prompt Caching via Embedding Similarity(@UC Berkeley)|[[pdf]](https://arxiv.org/pdf/2402.01173.pdf)|⚠️|⭐️⭐️ |  
 |2024.02|🔥🔥[Less] Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference(@CMU etc)|[[pdf]](https://arxiv.org/pdf/2402.09398.pdf)|⚠️|⭐️ |