Paper Citation Record · LEDGER

From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2407.11239.

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

pith.paper-citation-record.v1
2407.11239 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:58:46.617913Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T12:45:37.368172Z

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 c20078ba-f349-4cc3-a83a-8f194ff167f6 · inbound

Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN cites this paper.

Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-11T12:53:33.142019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9e535d5-52e1-4202-ab13-08472644b29d · inbound

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs cites this paper.

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T21:33:29.691119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cbe86d9-0b29-495b-aac8-e374e3dd741b · inbound

Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models cites this paper.

Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T21:31:36.145236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56d9ee7b-bcd1-435f-99cd-ea56ddb9ad75 · inbound

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models cites this paper.

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T15:36:04.436881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 494c96fc-f6d7-486f-8e95-9bbbc947e72b · inbound

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference cites this paper.

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-16T05:58:46.617913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50451dfa-18da-4b05-8c64-7f669f8bba9d · 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 From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:32:22.964473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372d7002-68de-496e-8601-1d6ca9672d0b · inbound

Memory-Efficient LLM Training by Various-Grained Low-Rank Projection of Gradients cites this paper.

Memory-Efficient LLM Training by Various-Grained Low-Rank Projection of Gradients From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T04:19:19.708663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbcac15b-02cc-4cad-858b-42fff4418d45 · inbound

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity cites this paper.

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T19:30:30.976347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 023937b8-2daa-4d79-872f-e23c85288eff · inbound

LOST: Low-rank and Sparse Pre-training for Large Language Models cites this paper.

LOST: Low-rank and Sparse Pre-training for Large Language Models From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T17:44:19.980700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b676826-9b17-4b04-b090-538dc0d1f1d4 · inbound

Accelerating Attention with Basis Decomposition cites this paper.

Accelerating Attention with Basis Decomposition From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T12:54:31.091978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c380c0bc-7622-4b41-93ec-11ecb2949cb3 · inbound

Geometrically Principled Randomized Optimization for Efficient LLM Training cites this paper.

Geometrically Principled Randomized Optimization for Efficient LLM Training From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T12:51:25.155303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b234c5ff-8a7a-46b3-84b3-70822a73f37d · inbound

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression cites this paper.

SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-15T12:45:37.370437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9e1f4ea6-7da9-41b6-a7a3-91fedb994ee1 · inbound

TIDE: Every Layer Knows the Token Beneath the Context cites this paper.

TIDE: Every Layer Knows the Token Beneath the Context From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:56:10.061257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e35cd850-9a20-4f6d-a820-8fd300780d6a · inbound

Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization cites this paper.

Pro-KLShampoo: Projected KL-Shampoo with Whitening Recovered by Orthogonalization From Low Rank Gradient Subspace Stabilization to Low-Rank Weights: Observations, Theories, and Applications

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:01:12.792211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.