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Data is the cornerstone of large language models (LLMs), but not all data is useful for model learning.
A mathematical theory of communication
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Prediction and entropy of printed English
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Scaling language models: Methods, analysis & insights from training gopher
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Training language models to follow instructions with human feedback
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Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks
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Alpagasus: Training a better alpaca with fewer data
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2023
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Ultrafeedback: Boosting language models with high-quality feedback
Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Wei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, and Maosong Sun. 2023 · 2023
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Language Modeling Is Compression
Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, and Joel Veness. 2023 · 2023
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Enhancing Chat Language Models by Scaling High-quality Instructional Conversations. In EMNLP . Association for Computational Linguistics, 3029–3051
Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou. 2023 · 2023
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Mods: Model-oriented data selection for instruction tuning
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Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2
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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 · 2023
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Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena. In NeurIPS
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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LIMA: Less Is More for Alignment. In NeurIPS
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A Survey on Data Selection for Language Models
Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, and William Yang Wang. 2024 · 2024
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Cited alongside, same era.
Ming Li, Yong Zhang, Zhitao Li, Jiuhai Chen, Lichang Chen, Ning Cheng, Jianzong Wang, Tianyi Zhou, and Jing Xiao. 2023 · 2023
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Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, and Junxian He. 2023 · 2023
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# InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models. In The Twelfth International Conference on Learning Representations
Keming Lu, Hongyi Yuan, Zheng Yuan, Runji Lin, Junyang Lin, Chuanqi Tan, Chang Zhou, and Jingren Zhou. 2023 · 2023
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Baolin Peng, Chunyuan Li, Pengcheng He, Michel Galley, and Jianfeng Gao. 2023 · 2023
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Verbosity bias in preference labeling by large language models
Keita Saito, Akifumi Wachi, Koki Wataoka, and Youhei Akimoto. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Data management for large language models: A survey
Zige Wang, Wanjun Zhong, Yufei Wang, Qi Zhu, Fei Mi, Baojun Wang, Lifeng Shang, Xin Jiang, and Qun Liu. 2023c · 2023
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Data selection for language models via importance resampling
Sang Michael Xie, Shibani Santurkar, Tengyu Ma, and Percy S Liang. 2023 · 2023
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Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, and Douwe Kiela. 2024 · 2024
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Compression Represents Intelligence Linearly
Yuzhen Huang, Jinghan Zhang, Zifei Shan, and Junxian He. 2024 · 2024
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Openassistant conversations-democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, et al · 2024
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Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning
Ming Li, Yong Zhang, Shwai He, Zhitao Li, Hongyu Zhao, Jianzong Wang, Ning Cheng, and Tianyi Zhou. 2024 · 2024
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Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller. 2024 · 2024
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gzip Predicts Data-dependent Scaling Laws
Rohan Pandey. 2024 · 2024
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Rethinking Data Selection for Supervised Fine-Tuning
Ming Shen. 2024 · 2024
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QuRating: Selecting High-Quality Data for Training Language Models
Alexander Wettig, Aatmik Gupta, Saumya Malik, and Danqi Chen. 2024 · 2024
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