Efficient Pre-Training of LLMs through Truncated SVD Layers | Paper Citation Record

Observation 803ca0db-dfff-419d-a183-a4fb9dd8a4d4 · outbound

This paper cites Princeton University Press, 2008.

Efficient Pre-Training of LLMs through Truncated SVD Layers Princeton University Press, 2008

Reference 1

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Observation eb999300-a5e4-4e24-8c8d-c2217c04322f · outbound

This paper cites GQA: Training generalized multi-query transformer models from multi-head checkpoints.

Efficient Pre-Training of LLMs through Truncated SVD Layers GQA: Training generalized multi-query transformer models from multi-head checkpoints

Reference 2

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This paper cites Unitary evolution recurrent neural networks, 2016.

Efficient Pre-Training of LLMs through Truncated SVD Layers Unitary evolution recurrent neural networks, 2016

Reference 3

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This paper cites Can we gain more from orthogonality regularizations in training deep cnns?, 2018.

Efficient Pre-Training of LLMs through Truncated SVD Layers Can we gain more from orthogonality regularizations in training deep cnns?, 2018

Reference 4

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This paper cites Cambridge University Press, 2023.

Efficient Pre-Training of LLMs through Truncated SVD Layers Cambridge University Press, 2023

Reference 5

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Reference 6

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Reference 7

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Observation 611fa5f3-172d-4acb-a452-19547ff7e3f0 · outbound

This paper cites Reducing overfitting in deep networks by decorrelating representations, 2016.

Efficient Pre-Training of LLMs through Truncated SVD Layers Reducing overfitting in deep networks by decorrelating representations, 2016

Reference 8

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This paper cites IOS Press, October 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers IOS Press, October 2024

Reference 9

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This paper cites Documenting large webtext corpora: A case study on the colossal clean crawled corpus, 2021.

Efficient Pre-Training of LLMs through Truncated SVD Layers Documenting large webtext corpora: A case study on the colossal clean crawled corpus, 2021

Reference 10

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This paper cites The Llama 3 Herd of Models.

Efficient Pre-Training of LLMs through Truncated SVD Layers The Llama 3 Herd of Models

Reference 11

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Observation 71be59f2-fb3a-44fb-8de5-47c194ac368b · outbound

This paper cites The approximation of one matrix by another of lower rank.

Efficient Pre-Training of LLMs through Truncated SVD Layers The approximation of one matrix by another of lower rank

Reference 12

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Observation 4888d7ca-8ad8-431e-938a-937d7a7f5710 · outbound

This paper cites Arias, and Steven T.

Efficient Pre-Training of LLMs through Truncated SVD Layers Arias, and Steven T

Reference 13

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Observation fcd53eef-4ceb-4e08-9487-bd379e41b4e2 · outbound

This paper cites Full-rank no more: Low-rank weight training for modern speech recognition models, 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers Full-rank no more: Low-rank weight training for modern speech recognition models, 2024

Reference 14

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Observation 813dba24-c7c6-4b33-8aeb-6b60d7b52e69 · outbound

This paper cites Deep feedforward networks.Deep learning, 1:161–217, 2016.

Efficient Pre-Training of LLMs through Truncated SVD Layers Deep feedforward networks.Deep learning, 1:161–217, 2016

Reference 15

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This paper cites From gpt to llama: Tracing the growth of large language models.Theoretical and Natural Science, 142:144–155, 11 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers From gpt to llama: Tracing the growth of large language models.Theoretical and Natural Science, 142:144–155, 11 2025

Reference 16

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This paper cites Sltrain: a sparse plus low-rank approach for parameter and memory efficient pretraining, 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers Sltrain: a sparse plus low-rank approach for parameter and memory efficient pretraining, 2024

Reference 17

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This paper cites Rae, Oriol Vinyals, and Laurent Sifre.

Efficient Pre-Training of LLMs through Truncated SVD Layers Rae, Oriol Vinyals, and Laurent Sifre

Reference 18

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This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Efficient Pre-Training of LLMs through Truncated SVD Layers Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 19

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Reference 20

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This paper cites Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei.

Efficient Pre-Training of LLMs through Truncated SVD Layers Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei

Reference 21

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This paper cites Initialization and regular- ization of factorized neural layers.

Efficient Pre-Training of LLMs through Truncated SVD Layers Initialization and regular- ization of factorized neural layers

Reference 22

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This paper cites Initialization and regular- ization of factorized neural layers, 2022.

Efficient Pre-Training of LLMs through Truncated SVD Layers Initialization and regular- ization of factorized neural layers, 2022

Reference 23

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This paper cites Lost: Low-rank and sparse pre-training for large language models, 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers Lost: Low-rank and sparse pre-training for large language models, 2025

Reference 24

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This paper cites Relora: High- rank training through low-rank updates, 2023.

Efficient Pre-Training of LLMs through Truncated SVD Layers Relora: High- rank training through low-rank updates, 2023

Reference 25

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This paper cites Cola: Compute-efficient pre-training of llms via low-rank activation, 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers Cola: Compute-efficient pre-training of llms via low-rank activation, 2025

Reference 26

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This paper cites Large language models: A survey, 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers Large language models: A survey, 2025

Reference 27

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This paper cites Parameter and memory efficient pretraining via low-rank riemannian optimization.

Efficient Pre-Training of LLMs through Truncated SVD Layers Parameter and memory efficient pretraining via low-rank riemannian optimization

Reference 28

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This paper cites Olmo 3.

Efficient Pre-Training of LLMs through Truncated SVD Layers Olmo 3

Reference 29

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This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

Efficient Pre-Training of LLMs through Truncated SVD Layers Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 30

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This paper cites Robust low-rank training via approximate orthonormal constraints, 2023.

Efficient Pre-Training of LLMs through Truncated SVD Layers Robust low-rank training via approximate orthonormal constraints, 2023

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This paper cites Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations, 2022.

Efficient Pre-Training of LLMs through Truncated SVD Layers Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations, 2022

Reference 32

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This paper cites Compact: Compressed activations for memory-efficient llm training, 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers Compact: Compressed activations for memory-efficient llm training, 2025

Reference 33

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This paper cites Cuttlefish: Low-Rank Model Training without All the Tuning.

Efficient Pre-Training of LLMs through Truncated SVD Layers Cuttlefish: Low-Rank Model Training without All the Tuning

Reference 34

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This paper cites Dynamic rank adjustment for accurate and efficient neural network training.arXiv preprint arXiv:2508.08625, 2025.

Efficient Pre-Training of LLMs through Truncated SVD Layers Dynamic rank adjustment for accurate and efficient neural network training.arXiv preprint arXiv:2508.08625, 2025

Reference 35

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This paper cites Elrt: Efficient low-rank training for compact convolutional neural networks, 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers Elrt: Efficient low-rank training for compact convolutional neural networks, 2024

Reference 36

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This paper cites Llama: Open and efficient foundation language models, 2023.

Efficient Pre-Training of LLMs through Truncated SVD Layers Llama: Open and efficient foundation language models, 2023

Reference 37

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This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Efficient Pre-Training of LLMs through Truncated SVD Layers Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 38

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This paper cites BOOST: BOttleneck-Optimized Scalable Training Framework for Low-Rank Large Language Models.

Efficient Pre-Training of LLMs through Truncated SVD Layers BOOST: BOttleneck-Optimized Scalable Training Framework for Low-Rank Large Language Models

Reference 39

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This paper cites Investigating low-rank training in transformer language models: Efficiency and scaling analysis, 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers Investigating low-rank training in transformer language models: Efficiency and scaling analysis, 2024

Reference 40

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Efficient Pre-Training of LLMs through Truncated SVD Layers Transformers: State-of-the-art natural language processing

Reference 41

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This paper cites Learning low-rank deep neural networks via singular vector orthogonality regularization and singular value sparsification, 2020.

Efficient Pre-Training of LLMs through Truncated SVD Layers Learning low-rank deep neural networks via singular vector orthogonality regularization and singular value sparsification, 2020

Reference 42

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This paper cites InRank: Incremental Low-Rank Learning.

Efficient Pre-Training of LLMs through Truncated SVD Layers InRank: Incremental Low-Rank Learning

Reference 43

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This paper cites Galore: Memory-efficient llm training by gradient low-rank projection, 2024.

Efficient Pre-Training of LLMs through Truncated SVD Layers Galore: Memory-efficient llm training by gradient low-rank projection, 2024

Reference 44

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This paper cites A survey of large language models, 2026.

Efficient Pre-Training of LLMs through Truncated SVD Layers A survey of large language models, 2026

Reference 45

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Efficient Pre-Training of LLMs through Truncated SVD Layers Hence the forward operator norm is controlled exactly byσ max

Reference 46

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Efficient Pre-Training of LLMs through Truncated SVD Layers Hence the backward operator norm is controlled by the same quantity

Reference 47

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This paper cites Likewise, ifδlies in the represented output subspacespan(U), then σmin√r ∥δ∥2 ≤ ∥W ⊤δ∥2 ≤ σmax√r ∥δ∥2.

Efficient Pre-Training of LLMs through Truncated SVD Layers Likewise, ifδlies in the represented output subspacespan(U), then σmin√r ∥δ∥2 ≤ ∥W ⊤δ∥2 ≤ σmax√r ∥δ∥2

Reference 48

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This paper cites If ui and vi denote the i-th columns of UandV, then W= 1√r rX i=1 σiuiv⊤ i , ∂L ∂σi = 1√r u⊤ i Gvi.

Efficient Pre-Training of LLMs through Truncated SVD Layers If ui and vi denote the i-th columns of UandV, then W= 1√r rX i=1 σiuiv⊤ i , ∂L ∂σi = 1√r u⊤ i Gvi

Reference 49

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Efficient Pre-Training of LLMs through Truncated SVD Layers Unresolved cited work

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This paper cites Orthonormality does not remove this fundamental low-rank bottleneck, but it does prevent additional instability caused by badly scaled basis factors.

Efficient Pre-Training of LLMs through Truncated SVD Layers Orthonormality does not remove this fundamental low-rank bottleneck, but it does prevent additional instability caused by badly scaled basis factors

Reference 52

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Efficient Pre-Training of LLMs through Truncated SVD Layers Unresolved cited work

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Efficient Pre-Training of LLMs through Truncated SVD Layers Unresolved cited work

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Efficient Pre-Training of LLMs through Truncated SVD Layers Unresolved cited work

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