Key papers

• Lora: Low-rank Adaptation Of Large Language Models (2021)
  Edward J. Hu, Yelong Shen, Phillip Wallis, et al.
  48.60
• Efficient Memory Management For Large Language Model Serving With Pagedattention (2023)
  Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, et al.
  46.56
• Efficient Streaming Language Models With Attention Sinks (2023)
  Guangxuan Xiao, Yuandong Tian, Beidi Chen, et al.
  37.76
• Llama: Open And Efficient Foundation Language Models (2023)
  Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.
  36.83
• Qlora: Efficient Finetuning Of Quantized Llms (2023)
  Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.
  36.23
• Minicpm: Unveiling The Potential Of Small Language Models With Scalable Training Strategies (2024)
  Shengding Hu, Yuge Tu, Xu Han, et al.
  36.01
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022)
  BigScience Workshop: Teven Le Scao, Angela Fan, Christopher Akiki, et al.
  33.79
• Layerskip: Enabling Early Exit Inference And Self-speculative Decoding (2024)
  Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.
  32.46
• Prefix-tuning: Optimizing Continuous Prompts For Generation (2021)
  Xiang Lisa Li, Percy Liang
  32.38
• Omniquant: Omnidirectionally Calibrated Quantization For Large Language Models (2023)
  Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, et al.
  31.92
• Training Compute-optimal Large Language Models (2022)
  Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, et al.
  31.52
• Deepseek LLM: Scaling Open-source Language Models With Longtermism (2024)
  Deepseek-Ai, :, Xiao Bi, et al.
  30.12
• Medusa: Simple LLM Inference Acceleration Framework With Multiple Decoding Heads (2024)
  Tianle Cai, Yuhong Li, Zhengyang Geng, et al.
  30.03
• LLM In A Flash: Efficient Large Language Model Inference With Limited Memory (2023)
  Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, et al.
  29.72
• Agentscope: A Flexible Yet Robust Multi-agent Platform (2024)
  Dawei Gao, Zitao Li, Xuchen Pan, et al.
  29.54
• Emergent Abilities Of Large Language Models (2022)
  Jason Wei, Yi Tay, Rishi Bommasani, et al.
  29.54
• Scaling Synthetic Data Creation With 1,000,000,000 Personas (2024)
  Tao Ge, Xin Chan, Xiaoyang Wang, et al.
  29.19
• Autogen: Enabling Next-gen LLM Applications Via Multi-agent Conversation (2023)
  Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.
  29.16
• Mobilellm: Optimizing Sub-billion Parameter Language Models For On-device Use Cases (2024)
  Zechun Liu, Changsheng Zhao, Forrest Iandola, et al.
  28.23
• Buffer Of Thoughts: Thought-augmented Reasoning With Large Language Models (2024)
  Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.
  27.84
• Duoattention: Efficient Long-context LLM Inference With Retrieval And Streaming Heads (2024)
  Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.
  27.44
• EASYTOOL: Enhancing Llm-based Agents With Concise Tool Instruction (2024)
  Siyu Yuan, Kaitao Song, Jiangjie Chen, et al.
  27.38
• Efficient Large Language Models: A Survey (2023)
  Zhongwei Wan, Xin Wang, Che Liu, et al.
  27.30
• Flashrag: A Modular Toolkit For Efficient Retrieval-augmented Generation Research (2024)
  Jiajie Jin, Yutao Zhu, Guanting Dong, et al.
  26.95
• Culturax: A Cleaned, Enormous, And Multilingual Dataset For Large Language Models In 167 Languages (2023)
  Thuat Nguyen, Chien van Nguyen, Viet Dac Lai, et al.
  26.68
• SOLAR 10.7B: Scaling Large Language Models With Simple Yet Effective Depth Up-scaling (2023)
  Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.
  26.34
• Triforce: Lossless Acceleration Of Long Sequence Generation With Hierarchical Speculative Decoding (2024)
  Hanshi Sun, Zhuoming Chen, Xinyu Yang, et al.
  26.11
• SVD-LLM: Truncation-aware Singular Value Decomposition For Large Language Model Compression (2024)
  Xin Wang, Yu Zheng, Zhongwei Wan, et al.
  25.83
• Memgpt: Towards Llms As Operating Systems (2023)
  Charles Packer, Sarah Wooders, Kevin Lin, et al.
  25.76
• Evoprompt: Connecting Llms With Evolutionary Algorithms Yields Powerful Prompt Optimizers (2023)
  Qingyan Guo, Rui Wang, Junliang Guo, et al.
  25.70
• When Scaling Meets LLM Finetuning: The Effect Of Data, Model And Finetuning Method (2024)
  Biao Zhang, Zhongtao Liu, Colin Cherry, et al.
  25.34
• MA-LMM: Memory-augmented Large Multimodal Model For Long-term Video Understanding (2024)
  Bo He, Hengduo Li, Young Kyun Jang, et al.
  24.50
• Federatedscope-llm: A Comprehensive Package For Fine-tuning Large Language Models In Federated Learning (2023)
  Weirui Kuang, Bingchen Qian, Zitao Li, et al.
  24.26
• Black-box Prompt Optimization: Aligning Large Language Models Without Model Training (2023)
  Jiale Cheng, Xiao Liu, Kehan Zheng, et al.
  23.78
• Routerbench: A Benchmark For Multi-llm Routing System (2024)
  Qitian Jason Hu, Jacob Bieker, Xiuyu Li, et al.
  23.73
• Tinybenchmarks: Evaluating Llms With Fewer Examples (2024)
  Felipe Maia Polo, Lucas Weber, Leshem Choshen, et al.
  23.68
• Discovering The Gems In Early Layers: Accelerating Long-context Llms With 1000x Input Token Reduction (2024)
  Zhenmei Shi, Yifei Ming, Xuan-Phi Nguyen, et al.
  23.61
• Cobra: Extending Mamba To Multi-modal Large Language Model For Efficient Inference (2024)
  Han Zhao, Min Zhang, Wei Zhao, et al.
  23.43
• GEAR: An Efficient KV Cache Compression Recipe For Near-lossless Generative Inference Of LLM (2024)
  Hao Kang, Qingru Zhang, Souvik Kundu, et al.
  23.22
• SPHINX-X: Scaling Data And Parameters For A Family Of Multi-modal Large Language Models (2024)
  Dongyang Liu, Renrui Zhang, Longtian Qiu, et al.
  23.22
• Cachegen: KV Cache Compression And Streaming For Fast Large Language Model Serving (2023)
  Yuhan Liu, Hanchen Li, Yihua Cheng, et al.
  23.13
• Expel: LLM Agents Are Experiential Learners (2023)
  Andrew Zhao, Daniel Huang, Quentin Xu, et al.
  23.10
• A Rank Stabilization Scaling Factor For Fine-tuning With Lora (2023)
  Damjan Kalajdzievski
  23.01
• Llava-phi: Efficient Multi-modal Assistant With Small Language Model (2024)
  Yichen Zhu, Minjie Zhu, Ning Liu, et al.
  22.96
• Reducing Transformer Key-value Cache Size With Cross-layer Attention (2024)
  William Brandon, Mayank Mishra, Aniruddha Nrusimha, et al.
  22.95
• A Survey On Self-evolution Of Large Language Models (2024)
  Zhengwei Tao, Ting-En Lin, Xiancai Chen, et al.
  22.85
• Stepcoder: Improve Code Generation With Reinforcement Learning From Compiler Feedback (2024)
  Shihan Dou, Yan Liu, Haoxiang Jia, et al.
  22.83
• Llms Can Easily Learn To Reason From Demonstrations Structure, Not Content, Is What Matters! (2025)
  Dacheng Li, Shiyi Cao, Tyler Griggs, et al.
  22.76
• A Survey On Model Compression For Large Language Models (2023)
  Xunyu Zhu, Jian Li, Yong Liu, et al.
  22.69
• Openfedllm: Training Large Language Models On Decentralized Private Data Via Federated Learning (2024)
  Rui Ye, Wenhao Wang, Jingyi Chai, et al.
  22.55
• Densemamba: State Space Models With Dense Hidden Connection For Efficient Large Language Models (2024)
  Wei He, Kai Han, Yehui Tang, et al.
  22.53
• Llumnix: Dynamic Scheduling For Large Language Model Serving (2024)
  Biao Sun, Ziming Huang, Hanyu Zhao, et al.
  22.35
• Duquant: Distributing Outliers Via Dual Transformation Makes Stronger Quantized Llms (2024)
  Haokun Lin, Haobo Xu, Yichen Wu, et al.
  22.34
• Memorag: Boosting Long Context Processing With Global Memory-enhanced Retrieval Augmentation (2024)
  Hongjin Qian, Zheng Liu, Peitian Zhang, et al.
  22.21
• In-context Vectors: Making In Context Learning More Effective And Controllable Through Latent Space Steering (2023)
  Sheng Liu, Haotian Ye, Lei Xing, et al.
  21.77
• Deepspeed-fastgen: High-throughput Text Generation For Llms Via MII And Deepspeed-inference (2024)
  Connor Holmes, Masahiro Tanaka, Michael Wyatt, et al.
  21.74
• Large Language Models For Compiler Optimization (2023)
  Chris Cummins, Volker Seeker, Dejan Grubisic, et al.
  21.62
• PB-LLM: Partially Binarized Large Language Models (2023)
  Yuzhang Shang, Zhihang Yuan, Qiang Wu, et al.
  21.48
• Shiftaddllm: Accelerating Pretrained Llms Via Post-training Multiplication-less Reparameterization (2024)
  Haoran You, Yipin Guo, Yichao Fu, et al.
  21.46
• Language Agents As Optimizable Graphs (2024)
  Mingchen Zhuge, Wenyi Wang, Louis Kirsch, et al.
  21.44