Low-rank Momentum Factorization for Memory Efficient Training | Paper Citation Record

Observation 3d091fdb-94ec-4d6e-8c7c-3f6b9ada94e2 · outbound

This paper cites Memory efficient adaptive optimization.

Low-rank Momentum Factorization for Memory Efficient Training Memory efficient adaptive optimization

Reference 1

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Observation b532b623-71d0-40f4-b010-b66bc957a580 · outbound

This paper cites Lower bounds for non-convex stochastic optimization.

Low-rank Momentum Factorization for Memory Efficient Training Lower bounds for non-convex stochastic optimization

Reference 2

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Observation 3fe12a6e-83c1-43dd-9681-700cffe0ce6e · outbound

This paper cites Modular Duality in Deep Learning.

Low-rank Momentum Factorization for Memory Efficient Training Modular Duality in Deep Learning

Reference 3

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This paper cites Old Optimizer, New Norm: An Anthology.

Low-rank Momentum Factorization for Memory Efficient Training Old Optimizer, New Norm: An Anthology

Reference 4

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This paper cites signsgd: Compressed optimisation for non-convex problems.

Low-rank Momentum Factorization for Memory Efficient Training signsgd: Compressed optimisation for non-convex problems

Reference 5

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Observation bbb69756-4f58-421b-9dca-bf1f25d5c1a4 · outbound

This paper cites Automatic Gradient Descent: Deep Learning without Hyperparameters.

Low-rank Momentum Factorization for Memory Efficient Training Automatic Gradient Descent: Deep Learning without Hyperparameters

Reference 6

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This paper cites Symbolic discovery of optimization algorithms.

Low-rank Momentum Factorization for Memory Efficient Training Symbolic discovery of optimization algorithms

Reference 7

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Observation 37add5ea-1f3f-4a0b-8e0b-d16bbe160b7b · outbound

This paper cites 8-bit Optimizers via Block-wise Quantization.

Low-rank Momentum Factorization for Memory Efficient Training 8-bit Optimizers via Block-wise Quantization

Reference 8

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Observation 1e8c6ba0-3238-45b3-965b-ea5cae56aedf · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

Low-rank Momentum Factorization for Memory Efficient Training Qlora: Efficient finetuning of quantized llms

Reference 9

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Observation 92ea956e-c64b-40a3-8cc9-9336f072b503 · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

Low-rank Momentum Factorization for Memory Efficient Training Adaptive subgradient methods for online learning and stochastic optimization

Reference 10

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Observation fba15dfa-01fe-458d-bf68-7558f6d01345 · outbound

This paper cites Combining axes preconditioners through kronecker approximation for deep learning.

Low-rank Momentum Factorization for Memory Efficient Training Combining axes preconditioners through kronecker approximation for deep learning

Reference 11

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Observation d8b1410a-a235-4978-bcc1-8cd76cb2083a · outbound

This paper cites Sketchy: Memory-efficient adaptive regularization with frequent directions.

Low-rank Momentum Factorization for Memory Efficient Training Sketchy: Memory-efficient adaptive regularization with frequent directions

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.800933Z

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Observation f3523b01-4493-4be9-9ec8-8377958da5fd · outbound

This paper cites Fast approximate natural gradient descent in a kronecker factored eigenbasis.

Low-rank Momentum Factorization for Memory Efficient Training Fast approximate natural gradient descent in a kronecker factored eigenbasis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.792974Z

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Observation 43c30931-6709-46ec-ba7b-63fdf9549231 · outbound

This paper cites Improving neural network training in low dimensional random bases.

Low-rank Momentum Factorization for Memory Efficient Training Improving neural network training in low dimensional random bases

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.785399Z

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Observation 46d2730b-4bb7-4c8c-83c8-1e7073e1420b · outbound

This paper cites A kronecker-factored approximate fisher matrix for convolution layers.

Low-rank Momentum Factorization for Memory Efficient Training A kronecker-factored approximate fisher matrix for convolution layers

Reference 15

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Observation d2334a67-9cef-41e9-bad2-19cb0492beaa · outbound

This paper cites OLMES: A Standard for Language Model Evaluations.

Low-rank Momentum Factorization for Memory Efficient Training OLMES: A Standard for Language Model Evaluations

Reference 16

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Observation cc7931f7-ca09-446e-b00e-37a06f26928d · outbound

This paper cites Shampoo: Preconditioned stochastic tensor optimization.

Low-rank Momentum Factorization for Memory Efficient Training Shampoo: Preconditioned stochastic tensor optimization

Reference 17

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Observation 71536acc-4a68-4f4f-bfcb-ea96cc205e28 · outbound

This paper cites Gradient Descent Happens in a Tiny Subspace.

Low-rank Momentum Factorization for Memory Efficient Training Gradient Descent Happens in a Tiny Subspace

Reference 18

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Observation 7d13c518-a176-44f3-a921-2569a2abe3a7 · outbound

This paper cites Flora: Low-Rank Adapters Are Secretly Gradient Compressors.

Low-rank Momentum Factorization for Memory Efficient Training Flora: Low-Rank Adapters Are Secretly Gradient Compressors

Reference 19

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Observation bd10f289-2c68-460e-b447-ed4f2b5479b8 · outbound

This paper cites Topics in matrix analysis.

Low-rank Momentum Factorization for Memory Efficient Training Topics in matrix analysis

Reference 20

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Observation a823097d-4846-4f24-9830-cd0abd3df947 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Low-rank Momentum Factorization for Memory Efficient Training Parameter-efficient transfer learning for nlp

Reference 21

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Observation 81fac90f-2158-41c7-b5b7-fdaa8185c668 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Low-rank Momentum Factorization for Memory Efficient Training LoRA: Low-Rank Adaptation of Large Language Models

Reference 22

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Observation 305cc2a1-a26b-4291-9bf4-8fd0fb450d06 · outbound

This paper cites modded-nanogpt: Speedrunning the nanogpt baseline, 2024 a.

Low-rank Momentum Factorization for Memory Efficient Training modded-nanogpt: Speedrunning the nanogpt baseline, 2024 a

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.751685Z

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Observation 86df6ef4-909a-4fda-b1dd-0e25d75367f4 · outbound

This paper cites Muon: An optimizer for hidden layers in neural networks, 2024 b.

Low-rank Momentum Factorization for Memory Efficient Training Muon: An optimizer for hidden layers in neural networks, 2024 b

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.743734Z

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Observation 705f936e-4b9c-4cdc-84c2-2819e351c7c1 · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA.

Low-rank Momentum Factorization for Memory Efficient Training A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 25

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Observation b05009ba-c43f-40bb-8ca5-f9d0c7d3d80f · outbound

This paper cites Scaling Laws for Neural Language Models.

Low-rank Momentum Factorization for Memory Efficient Training Scaling Laws for Neural Language Models

Reference 26

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Observation 70e53d3a-442f-4abb-aa35-4c9f769be0fb · outbound

This paper cites Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition.

Low-rank Momentum Factorization for Memory Efficient Training Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:35:40.577672Z

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Observation 58235faa-8bb5-44c0-b417-5c000c6c6e7f · outbound

This paper cites Kingma and Jimmy Ba.

Low-rank Momentum Factorization for Memory Efficient Training Kingma and Jimmy Ba

Reference 28

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Observation 5c145465-698e-4d14-940f-d61f01f4069e · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

Low-rank Momentum Factorization for Memory Efficient Training VeRA: Vector-based Random Matrix Adaptation

Reference 29

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Observation b72f3667-9544-45d7-a43d-53d61327f79e · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Low-rank Momentum Factorization for Memory Efficient Training Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 30

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Observation 33ae95ce-59c6-4ccc-a4b7-14e26ed11296 · outbound

This paper cites Scalable optimization in the modular norm.

Low-rank Momentum Factorization for Memory Efficient Training Scalable optimization in the modular norm

Reference 31

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Observation 48215550-78b8-43a5-ba07-9e7dadf5e798 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Low-rank Momentum Factorization for Memory Efficient Training The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 32

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Observation 7b5e13d4-b336-4951-b0b3-e6aac2eafcf5 · outbound

This paper cites Memory efficient optimizers with 4-bit states.

Low-rank Momentum Factorization for Memory Efficient Training Memory efficient optimizers with 4-bit states

Reference 33

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Observation cd7943ca-2435-4c8e-9273-49dbd1343839 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Low-rank Momentum Factorization for Memory Efficient Training Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 34

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Observation 805a5003-36a7-43bb-bef0-dc9b00e5268b · outbound

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

Low-rank Momentum Factorization for Memory Efficient Training Relora: High-rank training through low-rank updates

Reference 35

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Observation 2c3af3d2-a44b-4111-bd5e-3e79e5bc9429 · outbound

This paper cites On the limited memory bfgs method for large scale optimization.

Low-rank Momentum Factorization for Memory Efficient Training On the limited memory bfgs method for large scale optimization

Reference 36

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Observation 5bd23c7b-b0fa-4202-ba6c-cbb38d1c8ce9 · outbound

This paper cites Muon is Scalable for LLM Training.

Low-rank Momentum Factorization for Memory Efficient Training Muon is Scalable for LLM Training

Reference 37

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Observation 8e34f1bb-6d34-4aaa-b435-50c22f551eb7 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

Low-rank Momentum Factorization for Memory Efficient Training DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 38

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Observation bdd016c8-8623-473e-b4f0-d65feca6e5fd · outbound

This paper cites Decoupled Weight Decay Regularization.

Low-rank Momentum Factorization for Memory Efficient Training Decoupled Weight Decay Regularization

Reference 39

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Observation 41f8934f-c0ca-4531-9d2b-174c4e6cfcac · outbound

This paper cites BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models.

Low-rank Momentum Factorization for Memory Efficient Training BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models

Reference 40

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Observation bbe63c38-2c25-47b1-a48b-e8cd765c3073 · outbound

This paper cites CAME: Confidence-guided Adaptive Memory Efficient Optimization.

Low-rank Momentum Factorization for Memory Efficient Training CAME: Confidence-guided Adaptive Memory Efficient Optimization

Reference 41

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Observation 5758d07c-1abf-450f-9b2b-0ada3efa269a · outbound

This paper cites AdaLomo: Low-memory Optimization with Adaptive Learning Rate.

Low-rank Momentum Factorization for Memory Efficient Training AdaLomo: Low-memory Optimization with Adaptive Learning Rate

Reference 42

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Observation aa8b78af-79f6-4412-8c45-a7c3df309054 · outbound

This paper cites Full Parameter Fine-tuning for Large Language Models with Limited Resources.

Low-rank Momentum Factorization for Memory Efficient Training Full Parameter Fine-tuning for Large Language Models with Limited Resources

Reference 43

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Observation b33f2a32-f26b-4cab-bc92-e0b243e5deb4 · outbound

This paper cites SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training.

Low-rank Momentum Factorization for Memory Efficient Training SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training

Reference 44

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This paper cites New insights and perspectives on the natural gradient method.

Low-rank Momentum Factorization for Memory Efficient Training New insights and perspectives on the natural gradient method

Reference 45

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Observation 535a1cff-93fd-4595-b5dc-57ac99e1d34f · outbound

This paper cites Optimizing neural networks with kronecker-factored approximate curvature.

Low-rank Momentum Factorization for Memory Efficient Training Optimizing neural networks with kronecker-factored approximate curvature

Reference 46

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Observation d96bc255-68ef-4318-8d27-7152607d0cfa · outbound

This paper cites MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence.

Low-rank Momentum Factorization for Memory Efficient Training MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence

Reference 47

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Observation 3f9068b4-d42c-48fe-8539-1770cd4965d8 · outbound

This paper cites A New Perspective on Shampoo's Preconditioner.

Low-rank Momentum Factorization for Memory Efficient Training A New Perspective on Shampoo's Preconditioner

Reference 48

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Observation 1efd01c2-0826-46a9-bcfa-d986b1cb4467 · outbound

This paper cites Training language models to follow instructions with human feedback.

Low-rank Momentum Factorization for Memory Efficient Training Training language models to follow instructions with human feedback

Reference 49

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Observation 6f316196-de61-474c-baa8-f2798e19a7d8 · outbound

This paper cites The fineweb datasets: Decanting the web for the finest text data at scale.

Low-rank Momentum Factorization for Memory Efficient Training The fineweb datasets: Decanting the web for the finest text data at scale

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.688519Z

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Observation af92c5c3-9423-4e42-906b-a077d1a73022 · outbound

This paper cites Zero: Memory optimizations toward training trillion parameter models.

Low-rank Momentum Factorization for Memory Efficient Training Zero: Memory optimizations toward training trillion parameter models

Reference 51

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Observation 9adae0d8-c7be-4909-8e96-53e62d9dc309 · outbound

This paper cites Adarankgrad: Adaptive gradient-rank and moments for memory-efficient llms training and fine-tuning.

Low-rank Momentum Factorization for Memory Efficient Training Adarankgrad: Adaptive gradient-rank and moments for memory-efficient llms training and fine-tuning

Reference 52

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Observation 7e249672-1596-48c3-943e-0e72ef748e99 · outbound

This paper cites Ldadam: Adaptive optimization from low-dimensional gradient statistics.

Low-rank Momentum Factorization for Memory Efficient Training Ldadam: Adaptive optimization from low-dimensional gradient statistics

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.676755Z

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Observation b23d3601-7f59-4904-8d2e-0039c1fa3197 · outbound

This paper cites Gradient Multi-Normalization for Stateless and Scalable LLM Training.

Low-rank Momentum Factorization for Memory Efficient Training Gradient Multi-Normalization for Stateless and Scalable LLM Training

Reference 54

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Observation 34e4caf4-1165-4a4f-9045-929d96a595e8 · outbound

This paper cites Adafactor: Adaptive learning rates with sublinear memory cost.

Low-rank Momentum Factorization for Memory Efficient Training Adafactor: Adaptive learning rates with sublinear memory cost

Reference 55

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Observation 841a71e7-81fb-4fbb-85f4-c201c60929ff · outbound

This paper cites Tieleman and G.

Low-rank Momentum Factorization for Memory Efficient Training Tieleman and G

Reference 56

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Observation 110f4a2b-637f-488c-ae65-3bfc5ac28b6f · outbound

This paper cites Practical low-rank communication compression in decentralized deep learning.

Low-rank Momentum Factorization for Memory Efficient Training Practical low-rank communication compression in decentralized deep learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:35:40.657442Z

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Observation c37c9c3d-7ce6-4a10-95b5-e88c51857c64 · outbound

This paper cites SOAP: Improving and Stabilizing Shampoo using Adam.

Low-rank Momentum Factorization for Memory Efficient Training SOAP: Improving and Stabilizing Shampoo using Adam

Reference 58

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Observation 47ef6f09-ff35-46fa-80a5-2adbad33c61f · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

Low-rank Momentum Factorization for Memory Efficient Training GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T18:35:40.232517Z

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Observation 70c1579f-dfb6-489b-ae7b-dac080c96305 · outbound

This paper cites How far can camels go? exploring the state of instruction tuning on open resources.

Low-rank Momentum Factorization for Memory Efficient Training How far can camels go? exploring the state of instruction tuning on open resources

Reference 60

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Observation 0d750cd9-6d15-4d64-8b9f-3f5302b61e32 · outbound

This paper cites A Spectral Condition for Feature Learning.

Low-rank Momentum Factorization for Memory Efficient Training A Spectral Condition for Feature Learning

Reference 61

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Observation 44fa1c87-6636-4c72-b2e2-b83704a4c2f4 · outbound

This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

Low-rank Momentum Factorization for Memory Efficient Training Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 62

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Observation f90f451e-8e67-4718-ab89-7507bd97bf7f · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

Low-rank Momentum Factorization for Memory Efficient Training AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 63

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Observation ce95a6af-a70d-440f-91d7-1eabe494034a · outbound

This paper cites GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection.

Low-rank Momentum Factorization for Memory Efficient Training GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 64

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Observation 0b28fa6a-0895-48f6-8cb4-0bdc270963a8 · outbound

This paper cites Adapprox: Adaptive Approximation in Adam Optimization via Randomized Low-Rank Matrices.

Low-rank Momentum Factorization for Memory Efficient Training Adapprox: Adaptive Approximation in Adam Optimization via Randomized Low-Rank Matrices

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:35:40.307682Z

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Observation 008ee817-5a97-436a-97d1-a07d2e8019f7 · outbound

This paper cites APOLLO: SGD-like Memory, AdamW-level Performance.

Low-rank Momentum Factorization for Memory Efficient Training APOLLO: SGD-like Memory, AdamW-level Performance

Reference 66

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Observation 9b521a52-776b-4ec0-9b32-ea53ebece1f2 · outbound

This paper cites write newline.

Low-rank Momentum Factorization for Memory Efficient Training write newline

Reference 67

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