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Large language models (LLMs) encounter computational challenges during long-sequence inference, especially in the attention pre-filling phase, where the complexity grows quadratically with the prompt length.
Generating long sequences with sparse transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 1904
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Triton: an intermediate language and compiler for tiled neural network computations
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Big bird: Transformers for longer sequences
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On the expressive power of self-attention matrices
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Sparsebert: Rethinking the importance analysis in self-attention
Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, and James Tin-Yau Kwok · 2021
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Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Yu Lu, Shengfeng Pan, Bo Wen, and Yunfeng Liu · 2021
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2022
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∞ \infty -former: Infinite memory transformer
Pedro Henrique Martins, Zita Marinho, and André F. T. Martins · 2022
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William Brandon, Aniruddha Nrusimha, Kevin Qian, Zachary Ankner, Tian Jin, Zhiye Song, and Jonathan Ragan-Kelley · 2023
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Scaling transformer to 1m tokens and beyond with RMT
Aydar Bulatov, Yuri Kuratov, and Mikhail S. Burtsev · 2023
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Longnet: Scaling transformers to 1, 000, 000, 000 tokens
Jiayu Ding, Shuming Ma, Li Dong, Xingxing Zhang, Shaohan Huang, Wenhui Wang, Nanning Zheng, and Furu Wei · 2023
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Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
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Flashdecoding++: Faster large language model inference on gpus
Ke Hong, Guohao Dai, Jiaming Xu, Qiuli Mao, Xiuhong Li, Jun Liu, Kangdi Chen, Yuhan Dong, and Yu Wang · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Compressing context to enhance inference efficiency of large language models
Yucheng Li, Bo Dong, Frank Guerin, and Chenghua Lin · 2023
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Ring attention with blockwise transformers for near-infinite context
Hao Liu, Matei Zaharia, and Pieter Abbeel · 2023
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Landmark attention: Random-access infinite context length for transformers
Amirkeivan Mohtashami and Martin Jaggi · 2023
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RWKV: reinventing rnns for the transformer era
Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Stella Biderman, Huanqi Cao, Xin Cheng, Michael Chung, Leon Derczynski, Xingjian Du, Matteo Grella, Kranthi Kiran GV, Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Jiaju Lin, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Guangyu Song, Xiangru Tang, Johan S. Wind, Stanislaw Wozniak, Zhenyuan Zhang, Qinghua Zhou, Jian Zhu, and Rui-Jie Zhu · 2023
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Zeroscrolls: A zero-shot benchmark for long text understanding
Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, and Omer Levy · 2023
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Retentive network: A successor to transformer for large language models
Yutao Sun, Li Dong, Shaohan Huang, Shuming Ma, Yuqing Xia, Jilong Xue, Jianyong Wang, and Furu Wei · 2023
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Focused transformer: Contrastive training for context scaling
Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, and Piotr Milos · 2023
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H2O: heavy-hitter oracle for efficient generative inference of large language models
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Longllmlingua: Accelerating and enhancing llms in long context scenarios via prompt compression
Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, and Lili Qiu · 2024
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GEAR: an efficient KV cache compression recipe for near-lossless generative inference of LLM
Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, and Tuo Zhao · 2024
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Hip attention: Sparse sub-quadratic attention with hierarchical attention pruning
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Snapkv: LLM knows what you are looking for before generation
Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, and Deming Chen · 2024
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen · 2023
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Longbench: A bilingual, multitask benchmark for long context understanding
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xlstm: Extended long short-term memory
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Longlora: Efficient fine-tuning of long-context large language models
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Flashattention-2: Faster attention with better parallelism and work partitioning
Tri Dao · 2024
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Intactkv: Improving large language model quantization by keeping pivot tokens intact
Ruikang Liu, Haoli Bai, Haokun Lin, Yuening Li, Han Gao, Zhengzhuo Xu, Lu Hou, Jun Yao, and Chun Yuan · 2024
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KIVI: A tuning-free asymmetric 2bit quantization for KV cache
Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, and Xia Hu · 2024
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Leave no context behind: Efficient infinite context transformers with infini-attention
Tsendsuren Munkhdalai, Manaal Faruqui, and Siddharth Gopal · 2024
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Dynamic memory compression: Retrofitting llms for accelerated inference
Piotr Nawrot, Adrian Lancucki, Marcin Chochowski, David Tarjan, and Edoardo M. Ponti · 2024
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Llmlingua-2: Data distillation for efficient and faithful task-agnostic prompt compression
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, and Dongmei Zhang · 2024
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Llama 3 gradient: A series of long context models, 2024
Leonid Pekelis, Michael Feil, Forrest Moret, Mark Huang, and Tiffany Peng · 2024
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Yarn: Efficient context window extension of large language models
Bowen Peng, Jeffrey Quesnelle, Honglu Fan, and Enrico Shippole · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy P. Lillicrap, Jean-Baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, Ioannis Antonoglou, Rohan Anil, Sebastian Borgeaud, Andrew M. Dai, Katie Millican, Ethan Dyer, Mia Glaese, Thibault Sottiaux, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, James Molloy, Jilin Chen, Michael Isard, Paul Barham, Tom Hennigan, Ross McIlroy, Melvin Johnson, Johan Schalkwyk, Eli Collins, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, Clemens Meyer, Gregory Thornton, Zhen Yang, Henryk Michalewski, Zaheer Abbas, Nathan Schucher, Ankesh Anand, Richard Ives, James Keeling, Karel Lenc, Salem Haykal, Siamak Shakeri, Pranav Shyam, Aakanksha Chowdhery, Roman Ring, Stephen Spencer, Eren Sezener, and et al · 2024
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Sparq attention: Bandwidth-efficient LLM inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley, Charlie Blake, Carlo Luschi, and Douglas Orr · 2024
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Flashattention-3: Fast and accurate attention with asynchrony and low-precision
Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, and Tri Dao · 2024
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QUEST: query-aware sparsity for efficient long-context LLM inference
Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, and Song Han · 2024
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Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis · 2024
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Effective long-context scaling of foundation models
Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, and Hao Ma · 2024
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Retrieval meets long context large language models
Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, and Bryan Catanzaro · 2024
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