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Paper Citation Record · LEDGER

Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.16029.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2410.16029 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:59:48.049669Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-07T13:06:29.106206Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a964815e-6c11-4934-8371-7c97acad7c5c · inbound

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models cites this paper.

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-08T13:31:42.075566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:31:42.075566Z digest=sha256:4473fe561b2367d54da178c4f4580bd83c1f9efa2b4431e7e91f0ca64bd0b3ca

Observation 4f6ab72d-6886-4756-b985-5d3274e92f3c · inbound

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning

Reference 124

Resolution
unresolved
no resolver link, observed 2026-08-16T11:59:48.049669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:59:48.049669Z digest=sha256:0f91b36bb774924a181617d4e40f7fbb5e78d5e925503034b86b2c51dcc6e531

Observation 6f66875a-1ff1-4e6c-905f-4d83ba2ee424 · inbound

GaLore 2: Large-Scale LLM Pre-Training by Gradient Low-Rank Projection cites this paper.

GaLore 2: Large-Scale LLM Pre-Training by Gradient Low-Rank Projection Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T05:32:22.933329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:32:22.933329Z digest=sha256:1e2619330156981b3ac2d1bbeebf1fae7ee49bf0555a06f20da37d7121ae058e

Observation 4031ad15-2e78-486e-92b1-2d37bb73fdb4 · inbound

Scalable Parameter and Memory Efficient Pretraining for LLM: Recent Algorithmic Advances and Benchmarking cites this paper.

Scalable Parameter and Memory Efficient Pretraining for LLM: Recent Algorithmic Advances and Benchmarking Natural GaLore: Accelerating GaLore for memory-efficient LLM Training and Fine-tuning

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:06:29.184569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-07T13:06:23.613924Z digest=sha256:52a9984e75e1ffc580ad3501973edea99310c13f60f7aa522a75e0f3af9a766f