efficient_architecture_llm.md

Efficient Architecture of LLM

Title & Authors	Introduction	Links
Efficient Hybrid Inference for LLMs: Reward-Based Token Modelling with Selective Cloud Assistance Adarsh MS, Jithin VG, Ditto PS @Bud Ecosystem		Paper
Rethinking Optimization and Architecture for Tiny Language Models Yehui Tang, Fangcheng Liu, Yunsheng Ni, Yuchuan Tian, Zheyuan Bai, Yi-Qi Hu, Sichao Liu, Shangling Jui, Kai Han, Yunhe Wang		Github Paper
Tandem Transformers for Inference Efficient LLMs Aishwarya P S, Pranav Ajit Nair, Yashas Samaga, Toby Boyd, Sanjiv Kumar, Prateek Jain, Praneeth Netrapalli		Paper
Scaling Efficient LLMs B.N. Kausik		Paper
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases Zechun Liu, Changsheng Zhao, Forrest Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra		Paper
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding Benjamin Bergner, Andrii Skliar, Amelie Royer, Tijmen Blankevoort, Yuki Asano, Babak Ehteshami Bejnordi		Paper
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT Omkar Thawakar, Ashmal Vayani, Salman Khan, Hisham Cholakal, Rao M. Anwer, Michael Felsberg, Tim Baldwin, Eric P. Xing, Fahad Shahbaz Khan		Github Paper Model
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George Cristian-Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando De Freitas, Caglar Gulcehre		Paper
DiJiang: Efficient Large Language Models through Compact Kernelization Hanting Chen, Zhicheng Liu, Xutao Wang, Yuchuan Tian, Yunhe Wang		Github Paper
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou		Github Paper
Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin		Github Paper
Block Transformer: Global-to-Local Language Modeling for Fast Inference Namgyu Ho, Sangmin Bae, Taehyeon Kim, Hyunjik Jo, Yireun Kim, Tal Schuster, Adam Fisch, James Thorne, Se-Young Yun		Github Paper
Beyond KV Caching: Shared Attention for Efficient LLMs Bingli Liao, Danilo Vasconcellos Vargas		Github Paper
Efficient LLM Training and Serving with Heterogeneous Context Sharding among Attention Heads Xihui Lin, Yunan Zhang, Suyu Ge, Barun Patra, Vishrav Chaudhary, Xia Song		Github Paper
SentenceVAE: Enable Next-sentence Prediction for Large Language Models with Faster Speed, Higher Accuracy and Longer Context Hongjun An, Yifan Chen, Zhe Sun, Xuelong Li		Paper
Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions Zhihao He, Hang Yu, Zi Gong, Shizhan Liu, Jianguo Li, Weiyao Lin		Paper
Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin, Bing Li, Grace Li Zhang		Github Paper
SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs Yizhao Gao, Zhichen Zeng, Dayou Du, Shijie Cao, Hayden Kwok-Hay So, Ting Cao, Fan Yang, Mao Yang		Github Paper