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Built upon the Transformer, large language models (LLMs) have captured worldwide attention due to their remarkable abilities.
Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Randomized Positional Encodings Boost Length Generalization of Transformers
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, and Joel Veness. 2023 · 1903
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Syntactic structures
Noam Chomsky. 1957 · 1957
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Universal grammar
RICHARD MONTAGUE. 1970 · 1970
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Lei Jimmy Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton. 2016 · 2016
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot, Franck Gabriel, and Clement Hongler. 2018 · 2018
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Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
Brenden Lake and Marco Baroni. 2018 · 2018
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Extrapolation in NLP
Jeff Mitchell, Pontus Stenetorp, Pasquale Minervini, and Sebastian Riedel. 2018 · 2018
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Self-Attention with Relative Position Representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani. 2018 · 2018
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Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
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On the Relation between Position Information and Sentence Length in Neural Machine Translation
Masato Neishi and Naoki Yoshinaga. 2019 · 2019
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Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel
Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2019 · 2019
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Encoding word order in complex embeddings
Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang, and Jakob Grue Simonsen. 2019 · 2019
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Are Transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank Reddi, and Sanjiv Kumar. 2019 · 2019
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Location Attention for Extrapolation to Longer Sequences
Yann Dubois, Gautier Dagan, Dieuwke Hupkes, and Elia Bruni. 2020 · 2020
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Measuring Massive Multitask Language Understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2020
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Improve Transformer Models with Better Relative Position Embeddings
Zhiheng Huang, Davis Liang, Peng Xu, and Bing Xiang. 2020 · 2020
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Rethinking Positional Encoding in Language Pre-training
Guolin Ke, Di He, and Tie-Yan Liu. 2020 · 2020
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Learning to Encode Position for Transformer with Continuous Dynamical Model
Xuanqing Liu, Hsiang-Fu Yu, Inderjit Dhillon, and Cho-Jui Hsieh. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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On Position Embeddings in BERT
Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang, Qun Liu, and Jakob Grue Simonsen. 2020 · 2020
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PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter Liu. 2020 · 2020
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SHAPE: Shifted Absolute Position Embedding for Transformers
Shun Kiyono, Sosuke Kobayashi, Jun Suzuki, and Kentaro Inui. 2021 · 2021
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CAPE: Encoding Relative Positions with Continuous Augmented Positional Embeddings
Tatiana Likhomanenko, Qiantong Xu, Gabriel Synnaeve, Ronan Collobert, and Alex Rogozhnikov. 2021 · 2021
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Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Ofir Press, Noah Smith, and Mike Lewis. 2021 · 2021
Earlier work this paper cites.
Scale Efficiently: Insights from Pretraining and Finetuning Transformers
Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, and Donald Metzler. 2021 · 2021
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The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models
Ulme Wennberg and Gustav Eje Henter. 2021 · 2021
Earlier work this paper cites.
Exploring Length Generalization in Large Language Models
Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, and Behnam Neyshabur. 2022 · 2022
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Recurrent Memory Transformer
Aydar Bulatov, Yury Kuratov, and Mikhail Burtsev. 2022 · 2022
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KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation
Ta-Chung Chi, Ting-Han Fan, Peter J. Ramadge, and Alexander Rudnicky. 2022 · 2022
Cited alongside, same era.
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré. 2022 · 2022
Cited alongside, same era.
Position Information in Transformers: An Overview
Philipp Dufter, Martin Schmitt, and Hinrich Schütze. 2022 · 2022
Cited alongside, same era.
Efficiently Modeling Long Sequences with Structured State Spaces
Albert Gu, Karan Goel, and Christopher Ré. 2022 · 2022
Cited alongside, same era.
Transformer Language Models without Positional Encodings Still Learn Positional Information
Adi Haviv, Ori Ram, Ofir Press, Peter Izsak, and Omer Levy. 2022 · 2022
Cited alongside, same era.
ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding
Uri Shaham, Maor Ivgi, Avia Efrat, Jonathan Berant, and Omer Levy. 2023 · 2023
Closest in time.
Structured Packing in LLM Training Improves Long Context Utilization
Konrad Staniszewski, Szymon Tworkowski, Sebastian Jaszczur, Henryk Michalewski, Łukasz Kuciński, and Piotr Miłoś. 2023 · 2023
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A Length-Extrapolatable Transformer
Yutao Sun, Li Dong, Barun Patra, Shuming Ma, Shaohan Huang, Alon Benhaim, Vishrav Chaudhary, Xia Song, and Furu Wei. 2023 · 2023
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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. 2023 · 2023
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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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Show Your Work: Scratchpads for Intermediate Computation with Language Models
Maxwell Nye, Anders Johan Andreassen, Guy Gur-Ari, Henryk Michalewski, Jacob Austin, David Bieber, David Dohan, Aitor Lewkowycz, Maarten Bosma, David Luan, Charles Sutton, and Augustus Odena. 2022 · 2022
Cited alongside, same era.
Making Transformers Solve Compositional Tasks
Santiago Ontanon, Joshua Ainslie, Zachary Fisher, and Vaclav Cvicek. 2022 · 2022
Cited alongside, same era.
Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning
Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh. 2022 · 2022
Cited alongside, same era.
The Curious Case of Absolute Position Embeddings
Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, and Adina Williams. 2022 · 2022
Cited alongside, same era.
Efficient Transformers: A Survey
Yi Tay, Mostafa Dehghani, Dara Bahri, and Donald Metzler. 2022 · 2022
Cited alongside, same era.
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Generalization on the Unseen, Logic Reasoning and Degree Curriculum
Emmanuel Abbe, Samy Bengio, Aryo Lotfi, and Kevin Rizk. 2023 · 2023
Cited alongside, same era.
Closest in time.
What Algorithms can Transformers Learn? A Study in Length Generalization
Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Josh Susskind, Samy Bengio, and Preetum Nakkiran. 2023 · 2023
Closest in time.
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang, Yifan Song, Wenhao Wu, Furu Wei, and Sujian Li. 2023 · 2023
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Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Olatunji Ruwase, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, Ziyi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yunan Zhang, and Xiren Zhou. 2024 · 2024
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Accurate structure prediction of biomolecular interactions with AlphaFold 3
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J. Ballard, Joshua Bambrick, Sebastian W. Bodenstein, David A. Evans, Chia-Chun Hung, Michael O’Neill, David Reiman, Kathryn Tunyasuvunakool, Zachary Wu, Akvilė Žemgulytė, Eirini Arvaniti, Charles Beattie, Ottavia Bertolli, Alex Bridgland, Alexey Cherepanov, Miles Congreve, Alexander I. Cowen-Rivers, Andrew Cowie, Michael Figurnov, Fabian B. Fuchs, Hannah Gladman, Rishub Jain, Yousuf A. Khan, Caroline M. R. Low, Kuba Perlin, Anna Potapenko, Pascal Savy, Sukhdeep Singh, Adrian Stecula, Ashok Thillaisundaram, Catherine Tong, Sergei Yakneen, Ellen D. Zhong, Michal Zielinski, Augustin Žídek, Victor Bapst, Pushmeet Kohli, Max Jaderberg, Demis Hassabis, and John M. Jumper. 2024 · 2024
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Yi: Open Foundation Models by 01.AI
01 AI, Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Heng Li, Jiangcheng Zhu, Jianqun Chen, Jing Chang, Kaidong Yu, Peng Liu, Qiang Liu, Shawn Yue, Senbin Yang, Shiming Yang, Tao Yu, Wen Xie, Wenhao Huang, Xiaohui Hu, Xiaoyi Ren, Xinyao Niu, Pengcheng Nie, Yuchi Xu, Yudong Liu, Yue Wang, Yuxuan Cai, Zhenyu Gu, Zhiyuan Liu, and Zonghong Dai. 2024 · 2024
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Mistral NeMo
Mistral AI. 2024 · 2024
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L-Eval: Instituting Standardized Evaluation for Long Context Language Models
Chenxin An, Shansan Gong, Ming Zhong, Xingjian Zhao, Mukai Li, Jun Zhang, Lingpeng Kong, and Xipeng Qiu. 2024 · 2024
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LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding
Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, Yuxiao Dong, Jie Tang, and Juanzi Li. 2024 · 2024
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Toward Length-Extrapolatable Transformers
Ta-Chung Chi. 2024 · 2024
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LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, and Mao Yang. 2024 · 2024
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Gkamradt/LLMTest_NeedleInAHaystack
gkamradt. 2024 · 2024
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ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Dan Zhang, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, Hao Yu, Hongning Wang, Jiadai Sun, Jiajie Zhang, Jiale Cheng, Jiayi Gui, Jie Tang, Jing Zhang, Jingyu Sun, Juanzi Li, Lei Zhao, Lindong Wu, Lucen Zhong, Mingdao Liu, Minlie Huang, Peng Zhang, Qinkai Zheng, Rui Lu, Shuaiqi Duan, Shudan Zhang, Shulin Cao, Shuxun Yang, Weng Lam Tam, Wenyi Zhao, Xiao Liu, Xiao Xia, Xiaohan Zhang, Xiaotao Gu, Xin Lv, Xinghan Liu, Xinyi Liu, Xinyue Yang, Xixuan Song, Xunkai Zhang, Yifan An, Yifan Xu, Yilin Niu, Yuantao Yang, Yueyan Li, Yushi Bai, Yuxiao Dong, Zehan Qi, Zhaoyu Wang, Zhen Yang, Zhengxiao Du, Zhenyu Hou, and Zihan Wang. 2024 · 2024
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Contextual Position Encoding: Learning to Count What’s Important
Olga Golovneva, Tianlu Wang, Jason Weston, and Sainbayar Sukhbaatar. 2024 · 2024
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Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Di He, Jingjing Xu, Zhi Zhang, Hongxia Yang, and Liwei Wang. 2024 · 2024
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Can Perplexity Reflect Large Language Model’s Ability in Long Text Understanding?
Yutong Hu, Quzhe Huang, Mingxu Tao, Chen Zhang, and Yansong Feng. 2024 · 2024
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Repeat After Me: Transformers are Better than State Space Models at Copying
Samy Jelassi, David Brandfonbrener, Sham M. Kakade, and Eran Malach. 2024 · 2024
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Common 7B Language Models Already Possess Strong Math Capabilities
Chen Li, Weiqi Wang, Jingcheng Hu, Yixuan Wei, Nanning Zheng, Han Hu, Zheng Zhang, and Houwen Peng. 2024 · 2024
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Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Xingjian Du, Teddy Ferdinan, Haowen Hou, Przemysław Kazienko, Kranthi Kiran Gv, Jan Kocoń, Bartłomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanisław Woźniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, and Rui-Jie Zhu. 2024 · 2024
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Exploring Transformer Extrapolation
Zhen Qin, Yiran Zhong, and Hui Deng. 2024 · 2024
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On Context Utilization in Summarization with Large Language Models
Mathieu Ravaut, Aixin Sun, Nancy Chen, and Shafiq Joty. 2024 · 2024
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RoFormer: Enhanced transformer with Rotary Position Embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. 2024 · 2024
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Resonance RoPE: Improving Context Length Generalization of Large Language Models
Suyuchen Wang, Ivan Kobyzev, Peng Lu, Mehdi Rezagholizadeh, and Bang Liu. 2024 · 2024
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Zhaofeng Wu, Linlu Qiu, Alexis Ross, Ekin Akyürek, Boyuan Chen, Bailin Wang, Najoung Kim, Jacob Andreas, and Yoon Kim. 2024 · 2024
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A Theory for Length Generalization in Learning to Reason
Changnan Xiao and Bing Liu. 2024 · 2024
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CAPE: Context-Adaptive Positional Encoding for Length Extrapolation
Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael Ng, Xin Jiang, Zhenguo Li, and Yu Li. 2024 · 2024
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Transformers Can Achieve Length Generalization But Not Robustly
Yongchao Zhou, Uri Alon, Xinyun Chen, Xuezhi Wang, Rishabh Agarwal, and Denny Zhou. 2024 · 2024
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