Data pruning and neural scaling laws: fundamental limitations of
score-based algorithms

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Data pruning and neural scaling laws: fundamental limitations of score-based algorithms

14 February 2023

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Papers citing "Data pruning and neural scaling laws: fundamental limitations of score-based algorithms"

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Title
Efficient Alignment of Large Language Models via Data Sampling Amrit Khera Rajat Ghosh Debojyoti Dutta 149 1 0 15 Nov 2024
All models are wrong, some are useful: Model Selection with Limited Labels Patrik Okanovic Andreas Kirsch Jannes Kasper Torsten Hoefler Andreas Krause Nezihe Merve Gürel VLM 47 1 0 17 Oct 2024
Distilling the Knowledge in Data Pruning Emanuel Ben-Baruch Adam Botach Igor Kviatkovsky Manoj Aggarwal Gérard Medioni 70 2 0 12 Mar 2024
How to Train Data-Efficient LLMs Noveen Sachdeva Benjamin Coleman Wang-Cheng Kang Jianmo Ni Lichan Hong Ed H. Chi James Caverlee Julian McAuley D. Cheng 93 64 0 15 Feb 2024
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning Patrik Okanovic R. Waleffe Vasilis Mageirakos Konstantinos E. Nikolakakis Amin Karbasi Dionysis Kalogerias Nezihe Merve Gürel Theodoros Rekatsinas DD 104 14 0 28 May 2023
Data Distillation: A Survey Noveen Sachdeva Julian McAuley DD 92 78 0 11 Jan 2023
Contextual Diversity for Active Learning Sharat Agarwal H. Arora Saket Anand Chetan Arora 175 172 0 13 Aug 2020