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https://github.com/October2001/Awesome-KV-Cache-Compression
📰 Must-read papers on KV Cache Compression (constantly updating 🤗).
https://github.com/October2001/Awesome-KV-Cache-Compression
List: Awesome-KV-Cache-Compression
awesome-list large-language-models papers
Last synced: 2 months ago
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📰 Must-read papers on KV Cache Compression (constantly updating 🤗).
- Host: GitHub
- URL: https://github.com/October2001/Awesome-KV-Cache-Compression
- Owner: October2001
- License: mit
- Created: 2024-07-23T03:21:41.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-09-06T06:07:13.000Z (2 months ago)
- Last Synced: 2024-09-07T08:58:53.195Z (2 months ago)
- Topics: awesome-list, large-language-models, papers
- Homepage:
- Size: 501 KB
- Stars: 30
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- ultimate-awesome - Awesome-KV-Cache-Compression - 📰 Must-read papers on KV Cache Compression (constantly updating 🤗). (Other Lists / PowerShell Lists)
README
[](https://github.com/October2001/Awesome-KV-Cache-Compression/blob/main/LICENSE)
[](https://github.com/sindresorhus/awesome)
[](https://github.com/October2001/Awesome-KV-Cache-Compression/commits/main)
[](https://github.com/October2001/Awesome-KV-Cache-Compression/pulls)
[](https://github.com/October2001/Awesome-KV-Cache-Compression)
## 📢 News
🎉 [2024-07-23] Project Beginning 🥳
## 📜 Notice
This repository is constantly updating 🤗 ...
> You can directly click on the title to jump to the corresponding PDF link location
## 📷 Survey
1. [**Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption.**](https://arxiv.org/abs/2407.18003) *Shi Luohe, Zhang Hongyi, Yao Yao, Li Zuchao, Zhao Hai
.* COLM 2024.
## 🔍 Method
### 1️⃣ Pruning / Evicting / Sparse
1. [**Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time.**](https://arxiv.org/abs/2305.17118) *Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, Anshumali Shrivastava.* NeurIPS 2023.
2. [**SnapKV: LLM Knows What You are Looking for Before Generation.**](https://arxiv.org/abs/2404.14469) *Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen.* Arxiv 2024. [](https://github.com/FasterDecoding/SnapKV)
3. [**H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.**](https://arxiv.org/abs/2306.14048) *Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang Wang, Beidi Chen.* NeurIPS 2023. [](https://github.com/FMInference/H2O)
4. [**Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs.**](https://arxiv.org/abs/2310.01801) *Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao.* ICLR 2024.
5. [**PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference.**](https://arxiv.org/abs/2405.12532) *Dongjie Yang, XiaoDong Han, Yan Gao, Yao Hu, Shilin Zhang, Hai Zhao.* ACL 2024. [](https://github.com/mutonix/pyramidinfer)
6. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling.**](https://arxiv.org/abs/2406.02069) *Zefan Cai, Yichi Zhang, Bofei Gao, Yuliang Liu, Tianyu Liu, Keming Lu, Wayne Xiong, Yue Dong, Baobao Chang, Junjie Hu, Wen Xiao.* Arxiv 2024. [](https://github.com/Zefan-Cai/PyramidKV)
7. [**Transformers are Multi-State RNNs.**](https://arxiv.org/abs/2401.06104) *Matanel Oren, Michael Hassid, Nir Yarden, Yossi Adi, Roy Schwartz.* Arxiv 2024. [](https://github.com/schwartz-lab-NLP/TOVA)
8. [**Efficient Streaming Language Models with Attention Sinks.**](https://arxiv.org/abs/2309.17453) *Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis.* ICLR 2024. [](https://github.com/mit-han-lab/streaming-llm)
9. [**A Simple and Effective L2 Norm-Based Strategy for KV Cache Compression.**](https://arxiv.org/abs/2406.11430) *Alessio Devoto, Yu Zhao, Simone Scardapane, Pasquale Minervini.* Arxiv 2024.
10. [**Retrieval Head Mechanistically Explains Long-Context Factuality.**](https://arxiv.org/abs/2404.15574) *Wenhao Wu, Yizhong Wang, Guangxuan Xiao, Hao Peng, Yao Fu.* Arxiv 2024. [](https://github.com/nightdessert/Retrieval_Head)
11. [**Efficient Sparse Attention needs Adaptive Token Release.**](https://arxiv.org/abs/2407.02328) *Chaoran Zhang, Lixin Zou, Dan Luo, Min Tang, Xiangyang Luo, Zihao Li, Chenliang Li.* ACL 2024. [](https://github.com/WHUIR/ADORE)
12. [**Loki: Low-Rank Keys for Efficient Sparse Attention.**](https://arxiv.org/abs/2406.02542) *Prajwal Singhania, Siddharth Singh, Shwai He, Soheil Feizi, Abhinav Bhatele.* Arxiv 2024.
13. [**Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference.**](https://arxiv.org/abs/2402.09398) *Harry Dong, Xinyu Yang, Zhenyu Zhang, Zhangyang Wang, Yuejie Chi, Beidi Chen.* Arxiv 2024. [](https://github.com/hdong920/LESS)
14. [**ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching.**](https://arxiv.org/abs/2403.17312) *Youpeng Zhao, Di Wu, Jun Wang.* Arxiv 2024.
15. [**Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference.**](https://arxiv.org/abs/2403.09054) *Muhammad Adnan, Akhil Arunkumar, Gaurav Jain, Prashant J. Nair, Ilya Soloveychik, Purushotham Kamath.* Arxiv 2024. [](https://github.com/d-matrix-ai/keyformer-llm)
16. [**Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference.**](https://arxiv.org/abs/2407.11550) *Yuan Feng, Junlin Lv, Yukun Cao, Xike Xie, S. Kevin Zhou.* Arxiv 2024. [](https://github.com/FFY0/AdaKV)
17. [**Attention Score is not All You Need for Token Importance Indicator in KV Cache Reduction: Value Also Matters.**](https://arxiv.org/abs/2406.12335) *Zhiyu Guo, Hidetaka Kamigaito, Taro Watanabe.* Arxiv 2024.
18. [**On the Efficacy of Eviction Policy for Key-Value Constrained Generative Language Model Inference.**](https://arxiv.org/abs/2406.12335) *Siyu Ren, Kenny Q. Zhu.* Arxiv 2024. [](https://github.com/DRSY/EasyKV)
19. [**CORM: Cache Optimization with Recent Message for Large Language Model Inference.**](https://arxiv.org/abs/2404.15949) *Jincheng Dai, Zhuowei Huang, Haiyun Jiang, Chen Chen, Deng Cai, Wei Bi, Shuming Shi.* Arxiv 2024.
20. [**RazorAttention: Efficient KV Cache Compression Through Retrieval Heads.**](https://www.arxiv.org/abs/2407.15891) *Hanlin Tang, Yang Lin, Jing Lin, Qingsen Han, Shikuan Hong, Yiwu Yao, Gongyi Wang.* Arxiv 2024.
21. [**ThinK: Thinner Key Cache by Query-Driven Pruning.**](https://arxiv.org/abs/2407.21018) *Yuhui Xu, Zhanming Jie, Hanze Dong, Lei Wang, Xudong Lu, Aojun Zhou, Amrita Saha, Caiming Xiong, Doyen Sahoo.* Arxiv 2024.
22. [**A2SF: Accumulative Attention Scoring with Forgetting Factor for Token Pruning in Transformer Decoder.**](https://arxiv.org/abs/2407.20485) *Hyun Rae Jo, Dong Kun Shin.* Arxiv 2024. [](https://github.com/Dirac-Notation/A2SF)
23. [**Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference.**](https://arxiv.org/abs/2406.10774) *Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, Song Han.* Arxiv 2024. [](https://github.com/mit-han-lab/Quest)
24. [**LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference.**](https://arxiv.org/abs/2407.14057) *Qichen Fu, Minsik Cho, Thomas Merth, Sachin Mehta, Mohammad Rastegari, Mahyar Najibi.* Arxiv 2024.
25. [**NACL: A General and Effective KV Cache Eviction Framework for LLMs at Inference Time.**](https://arxiv.org/abs/2408.03675) *Yilong Chen, Guoxia Wang, Junyuan Shang, Shiyao Cui, Zhenyu Zhang, Tingwen Liu, Shuohuan Wang, Yu Sun, Dianhai Yu, Hua Wu.* ACL 2024. [](https://github.com/PaddlePaddle/Research/tree/master/NLP/ACL2024-NACL)
26. [**Post-Training Sparse Attention with Double Sparsity.**](https://arxiv.org/abs/2408.07092) *Shuo Yang, Ying Sheng, Joseph E. Gonzalez, Ion Stoica, Lianmin Zheng.* Arxiv 2024. [](https://github.com/andy-yang-1/DoubleSparse)
27. [**Farewell to Length Extrapolation, a Training-Free Infinite Context with Finite Attention Scope.**](https://www.arxiv.org/abs/2407.15176) *Xiaoran Liu, Qipeng Guo, Yuerong Song, Zhigeng Liu, Kai Lv, Hang Yan, Linlin Li, Qun Liu, Xipeng Qiu.* Arxiv 2024.
28. [**Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference.**](https://arxiv.org/abs/2403.09636) *Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski, David Tarjan, Edoardo M. Ponti.* Arxiv 2024.
29. [**MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention.**](https://arxiv.org/abs/2407.02490) *Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, Qianhui Wu, Xufang Luo, Surin Ahn, Zhenhua Han, Amir H. Abdi, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu.* Arxiv 2024. [](https://github.com/microsoft/MInference)
30. [**Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers.**](https://arxiv.org/abs/2305.15805) *Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann.* NeurIPS 2023.
### 2️⃣ Merging
1. [**D2O: Dynamic Discriminative Operations for Efficient Generative Inference of Large Language Models.**](https://arxiv.org/abs/2406.13035) *Zhongwei Wan, Xinjian Wu, Yu Zhang, Yi Xin, Chaofan Tao, Zhihong Zhu, Xin Wang, Siqi Luo, Jing Xiong, Mi Zhang.* Arxiv 2024.
2. [**Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks.**](https://arxiv.org/abs/2407.08454) *Zheng Wang, Boxiao Jin, Zhongzhi Yu, Minjia Zhang.* Arxiv 2024.
3. [**CaM: Cache Merging for Memory-efficient LLMs Inference.**](https://openreview.net/forum?id=LCTmppB165) *Yuxin Zhang, Yuxuan Du, Gen Luo, Yunshan Zhong, Zhenyu Zhang, Shiwei Liu, Rongrong Ji.* ICML 2024. [](https://github.com/zyxxmu/cam)
4. [**Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs.**](https://arxiv.org/abs/2404.10308) *Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin.* ICLR 2024. [](https://github.com/alinlab/HOMER)
5. [**Token Merging: Your ViT But Faster.**](https://arxiv.org/abs/2210.09461) *Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, Judy Hoffman.* ICLR 2023. [](https://github.com/facebookresearch/ToMe)
### 3️⃣ Cross-Layer
1. [**You Only Cache Once: Decoder-Decoder Architectures for Language Models.**](https://arxiv.org/abs/2405.05254) *Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei.* Arxiv 2024. [](https://github.com/microsoft/unilm)
2. [**Reducing Transformer Key-Value Cache Size with Cross-Layer Attention.**](https://arxiv.org/abs/2405.12981) *William Brandon, Mayank Mishra, Aniruddha Nrusimha, Rameswar Panda, Jonathan Ragan Kelly.* Arxiv 2024.
3. [**Layer-Condensed KV Cache for Efficient Inference of Large Language Models.**](https://arxiv.org/abs/2405.10637) *Haoyi Wu, Kewei Tu.* Arxiv 2024. [](https://github.com/whyNLP/LCKV)
4. [**MiniCache: KV Cache Compression in Depth Dimension for Large Language Models.**](https://arxiv.org/abs/2405.14366) *Akide Liu, Jing Liu, Zizheng Pan, Yefei He, Gholamreza Haffari, Bohan Zhuang.* Arxiv 2024.
5. [**MLKV: Multi-Layer Key-Value Heads for Memory Efficient Transformer Decoding.**](https://arxiv.org/abs/2406.09297) *Zayd Muhammad Kawakibi Zuhri, Muhammad Farid Adilazuarda, Ayu Purwarianti, Alham Fikri Aji.* Arxiv 2024. [](https://github.com/zaydzuhri/pythia-mlkv)
### 4️⃣ Low-Rank
1. [**GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.**](https://arxiv.org/abs/2305.13245) *Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, Sumit Sanghai.* EMNLP 2023.
2. [**DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.**](https://arxiv.org/abs/2405.04434) *DeepSeek-AI.* Arxiv 2024. [](https://github.com/deepseek-ai/DeepSeek-V2)
3. [**Effectively Compress KV Heads for LLM.**](https://arxiv.org/abs/2406.07056) *Hao Yu, Zelan Yang, Shen Li, Yong Li, Jianxin Wu.* Arxiv 2024.
### 5️⃣ Quantization
1. [**ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification.**](https://www.arxiv.org/abs/2405.14256) *Yefei He, Luoming Zhang, Weijia Wu, Jing Liu, Hong Zhou, Bohan Zhuang.* Arxiv 2024.
2. [**No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization.**](https://arxiv.org/abs/2402.18096) *June Yong Yang, Byeongwook Kim, Jeongin Bae, Beomseok Kwon, Gunho Park, Eunho Yang, Se Jung Kwon, Dongsoo Lee.* Arxiv 2024.
3. [**KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache.**](https://arxiv.org/abs/2402.02750) *Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu.* Arxiv 2024. [](https://github.com/jy-yuan/KIVI)
4. [**GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM.**](https://arxiv.org/abs/203.05527) *Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao.* Arxiv 2024. [](https://github.com/opengear-project/GEAR)
5. [**PQCache: Product Quantization-based KVCache for Long Context LLM Inference.**](https://arxiv.org/abs/2407.12820) *Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui.* Arxiv 2024.
6. [**Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression.**](https://arxiv.org/abs/2405.12591) *Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Yipeng Ma, Tao Wang, Ji-Rong Wen.* Arxiv 2024.
7. [**SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models.**](https://arxiv.org/abs/2405.06219) *Haojie Duanmu, Zhihang Yuan, Xiuhong Li, Jiangfei Duan, Xingcheng Zhang, Dahua Lin.* Arxiv 2024. [](https://github.com/cat538/SKVQ)
8. [**QAQ: Quality Adaptive Quantization for LLM KV Cache.**](https://arxiv.org/abs/2403.04643) *Shichen Dong, Wen Cheng, Jiayu Qin, Wei Wang.* Arxiv 2024. [](https://github.com/ClubieDong/QAQ-KVCacheQuantization)
9. [**KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization.**](https://arxiv.org/abs/2401.18079) *Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Michael W. Mahoney, Yakun Sophia Shao, Kurt Keutzer, Amir Gholami.* Arxiv 2024. [](https://github.com/SqueezeAILab/KVQuant)
10. [**WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More.**](https://arxiv.org/abs/2402.12065) *Yuxuan Yue, Zhihang Yuan, Haojie Duanmu, Sifan Zhou, Jianlong Wu, Liqiang Nie.* Arxiv 2024.
### 6️⃣ Prompt Compression
1. [**LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models.**](https://arxiv.org/abs/2310.05736) *Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang, Lili Qiu.* EMNLP 2023. [](https://github.com/microsoft/LLMLingua)
2. [**LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression.**](https://arxiv.org/abs/2403.12968) *Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin, Victor Rühle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang.* ACL 2024. [](https://github.com/microsoft/LLMLingua)
3. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression.**](https://arxiv.org/abs/2310.06839) *Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu.* ACL 2024. [](https://github.com/microsoft/LLMLingua)
## 📊 Evaluation
1. [**KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches.**](https://arxiv.org/abs/2407.01527) *Jiayi Yuan, Hongyi Liu, Shaochen (Henry)Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Hu.* Arxiv 2024.