LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang, Lili Qiu |
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Github Paper |
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, Lili Qiu |
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EntropyRank: Unsupervised Keyphrase Extraction via Side-Information Optimization for Language Model-based Text Compression Alexander Tsvetkov. Alon Kipnis |
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LLMZip: Lossless Text Compression using Large Language Models Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan, Dileep Kalathil, Jean-Francois Chamberland, Srinivas Shakkottai |
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Paper | Unofficial Github |
Adapting Language Models to Compress Contexts Alexis Chevalier, Alexander Wettig, Anirudh Ajith, Danqi Chen |
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Github Paper |
In-context Autoencoder for Context Compression in a Large Language Model Tao Ge, Jing Hu, Xun Wang, Si-Qing Chen, Furu Wei |
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Nugget 2D: Dynamic Contextual Compression for Scaling Decoder-only Language Model Guanghui Qin, Corby Rosset, Ethan C. Chau, Nikhil Rao, Benjamin Van Durme |
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Boosting LLM Reasoning: Push the Limits of Few-shot Learning with Reinforced In-Context Pruning Xijie Huang, Li Lyna Zhang, Kwang-Ting Cheng, Mao Yang |
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ProPD: Dynamic Token Tree Pruning and Generation for LLM Parallel Decoding Shuzhang Zhong, Zebin Yang, Meng Li, Ruihao Gong, Runsheng Wang, Ru Huang |
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Learning to Compress Prompt in Natural Language Formats Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Hu |
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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 et al |
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PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models Jinyi Li, Yihuai Lan, Lei Wang, Hao Wang |
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Github Paper |
PROMPT-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression Muhammad Asif Ali, Zhengping Li, Shu Yang, Keyuan Cheng, Yang Cao, Tianhao Huang, Lijie Hu, Lu Yu, Di Wang |
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Training LLMs over Neurally Compressed Text Brian Lester, Jaehoon Lee, Alex Alemi, Jeffrey Pennington, Adam Roberts, Jascha Sohl-Dickstein, Noah Constant |
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Adapting LLMs for Efficient Context Processing through Soft Prompt Compression Cangqing Wang, Yutian Yang, Ruisi Li, Dan Sun, Ruicong Cai, Yuzhu Zhang, Chengqian Fu, Lillian Floyd |
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Rethinking LLM Memorization through the Lens of Adversarial Compression Avi Schwarzschild, Zhili Feng, Pratyush Maini, Zachary C. Lipton, J. Zico Kolter |
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Github Paper Project |
Brevity is the soul of wit: Pruning long files for code generation Aaditya K. Singh, Yu Yang, Kushal Tirumala, Mostafa Elhoushi, Ari S. Morcos |
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PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning Jiaru Zou, Mengyu Zhou, Tao Li, Shi Han, Dongmei Zhang |
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Entropy Law: The Story Behind Data Compression and LLM Performance Mingjia Yin, Chuhan Wu, Yufei Wang, Hao Wang, Wei Guo, Yasheng Wang, Yong Liu, Ruiming Tang, Defu Lian, Enhong Chen |
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Characterizing Prompt Compression Methods for Long Context Inference Siddharth Jha, Lutfi Eren Erdogan, Sehoon Kim, Kurt Keutzer, Amir Gholami |
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QUITO: Accelerating Long-Context Reasoning through Query-Guided Context Compression Wenshan Wang, Yihang Wang, Yixing Fan, Huaming Liao, Jiafeng Guo |
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Github Paper |
500xCompressor: Generalized Prompt Compression for Large Language Models Zongqian Li, Yixuan Su, Nigel Collier |
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Github Paper |
Enhancing and Accelerating Large Language Models via Instruction-Aware Contextual Compression Haowen Hou, Fei Ma, Binwen Bai, Xinxin Zhu, Fei Yu |
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Github Paper |
Efficient LLM Context Distillation Rajesh Upadhayayaya, Zachary Smith, Chritopher Kottmyer, Manish Raj Osti |
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TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning Shivam Shandilya, Menglin Xia, Supriyo Ghosh, Huiqiang Jiang, Jue Zhang, Qianhui Wu, Victor Rühle |
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AlphaZip: Neural Network-Enhanced Lossless Text Compression Swathi Shree Narashiman, Nitin Chandrachoodan |
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Github Paper |
Parse Trees Guided LLM Prompt Compression Wenhao Mao, Chengbin Hou, Tianyu Zhang, Xinyu Lin, Ke Tang, Hairong Lv |
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Github Paper |
FineZip : Pushing the Limits of Large Language Models for Practical Lossless Text Compression Fazal Mittu, Yihuan Bu, Akshat Gupta, Ashok Devireddy, Alp Eren Ozdarendeli, Anant Singh, Gopala Anumanchipalli |
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Github Paper |
Perception Compressor:A training-free prompt compression method in long context scenarios Jiwei Tang, Jin Xu, Tingwei Lu, Hai Lin, Yiming Zhao, Hai-Tao Zheng |
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From Reading to Compressing: Exploring the Multi-document Reader for Prompt Compression Eunseong Choi, Sunkyung Lee, Minjin Choi, June Park, Jongwuk Lee |
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Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferability Tsz Ting Chung, Leyang Cui, Lemao Liu, Xinting Huang, Shuming Shi, Dit-Yan Yeung |
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MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compression Noel Elias, Homa Esfahanizadeh, Kaan Kale, Sriram Vishwanath, Muriel Medard |
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