LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning

Exponential smoothing: The state of the art

Everette S Gardner Jr. 1985 · 1985

Earlier work this paper cites.

The nonstochastic multiarmed bandit problem

Peter Auer, Nicolo Cesa-Bianchi, Yoav Freund, and Robert E Schapire. 2002 · 2002

Earlier work this paper cites.

Multi-armed bandit algorithms and empirical evaluation. In European conference on machine learning . Springer, 437–448

Joannes Vermorel and Mehryar Mohri. 2005 · 2005

Earlier work this paper cites.

Snorkel: Rapid training data creation with weak supervision. In Proceedings of the VLDB endowment. International conference on very large data bases , Vol. 11. 269

Alexander Ratner, Stephen H Bach, Henry Ehrenberg, Jason Fries, Sen Wu, and Christopher Ré. 2017 · 2017

Earlier work this paper cites.

Active Learning for Convolutional Neural Networks: A Core-Set Approach. In International Conference on Learning Representations

Ozan Sener and Silvio Savarese. 2018 · 2018

Earlier work this paper cites.

Data shapley: Equitable valuation of data for machine learning. In International conference on machine learning . PMLR, 2242–2251

Amirata Ghorbani and James Zou. 2019 · 2019

Earlier work this paper cites.

Human-in-the-loop Outlier Detection. In SIGMOD Conference . ACM, 19–33

Chengliang Chai, Lei Cao, Guoliang Li, Jian Li, Yuyu Luo, and Samuel Madden. 2020 · 2020

Earlier work this paper cites.

TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages

Jonathan H Clark, Eunsol Choi, Michael Collins, Dan Garrette, Tom Kwiatkowski, Vitaly Nikolaev, and Jennimaria Palomaki. 2020 · 2020

Earlier work this paper cites.

VisClean: Interactive Cleaning for Progressive Visualization

Yuyu Luo, Chengliang Chai, Xuedi Qin, Nan Tang, and Guoliang Li. 2020b · 2020

Earlier work this paper cites.

Making data visualization more efficient and effective: a survey

Xuedi Qin, Yuyu Luo, Nan Tang, and Guoliang Li. 2020 · 2020

Earlier work this paper cites.

Evaluating large language models trained on code

Original

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021

Earlier work this paper cites.

Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021

Earlier work this paper cites.

Measuring mathematical problem solving with the math dataset

Original

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

Earlier work this paper cites.

Selective data acquisition in the wild for model charging

Chengliang Chai, Jiabin Liu, Nan Tang, Guoliang Li, and Yuyu Luo. 2022 · 2022

Earlier work this paper cites.

Unnatural instructions: Tuning language models with (almost) no human labor

Original

Or Honovich, Thomas Scialom, Omer Levy, and Timo Schick. 2022 · 2022

Earlier work this paper cites.

Lora: Low-rank adaptation of large language models

Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2022

Earlier work this paper cites.

Feature augmentation with reinforcement learning. In 2022 IEEE 38th International Conference on Data Engineering (ICDE) . IEEE, 3360–3372

Jiabin Liu, Chengliang Chai, Yuyu Luo, Yin Lou, Jianhua Feng, and Nan Tang. 2022 · 2022

Earlier work this paper cites.

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023

Earlier work this paper cites.

Instruction mining: Instruction data selection for tuning large language models

Original

Yihan Cao, Yanbin Kang, Chi Wang, and Lichao Sun. 2023 · 2023

Earlier work this paper cites.

Goodcore: Data-effective and data-efficient machine learning through coreset selection over incomplete data

Chengliang Chai, Jiabin Liu, Nan Tang, Ju Fan, Dongjing Miao, Jiayi Wang, Yuyu Luo, and Guoliang Li. 2023a · 2023

Cited alongside, same era.

Data Management for Machine Learning: A Survey

Chengliang Chai, Jiayi Wang, Yuyu Luo, Zeping Niu, and Guoliang Li. 2023c · 2023

Cited alongside, same era.

Code alpaca: An instruction-following llama model for code generation

Sahil Chaudhary. 2023 · 2023

Cited alongside, same era.

Alpagasus: Training a better alpaca with fewer data

Original

Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, et al · 2023

Cited alongside, same era.

Enhancing Chat Language Models by Scaling High-quality Instructional Conversations. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing . 3029–3051

Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou. 2023 · 2023

From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) . 7595–7628

Ming Li, Yong Zhang, Zhitao Li, Jiuhai Chen, Lichang Chen, Ning Cheng, Jianzong Wang, Tianyi Zhou, and Jing Xiao. 2024e · 2024

Later among the works it cites.

Instruction Embedding: Latent Representations of Instructions Towards Task Identification

Yiwei Li, Jiayi Shi, Shaoxiong Feng, Peiwen Yuan, Xinglin Wang, Boyuan Pan, Heda Wang, and Yao Hu. 2024c · 2024

Later among the works it cites.

Selectit: Selective instruction tuning for large language models via uncertainty-aware self-reflection

Original

Liangxin Liu, Xuebo Liu, Derek F Wong, Dongfang Li, Ziyi Wang, Baotian Hu, and Min Zhang. 2024a · 2024

Later among the works it cites.

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 15725–15788