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Paper Citation Record · LEDGER

Compressing Large Language Models using Low Rank and Low Precision Decomposition

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.18886.

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

pith.paper-citation-record.v1
2405.18886 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:35:26.812498Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 72936bd6-9e74-44a5-a39e-41b7cd4c47e2 · inbound

Low-Rank Correction for Quantized LLMs cites this paper.

Low-Rank Correction for Quantized LLMs Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T18:35:26.812498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:35:26.812498Z digest=sha256:3dfd8147abcc336ac5df5f53e322cbd300bc7c34ac7e59e9ff7dc59f447b4eb0

Observation 359ac8eb-a30c-4602-91a7-c8aad07a4551 · inbound

On Accelerating Edge AI: Optimizing Resource-Constrained Environments cites this paper.

On Accelerating Edge AI: Optimizing Resource-Constrained Environments Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T14:46:38.348825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:46:38.348825Z digest=sha256:390a650f203cd8765192f0a4b8ce6d7893b1376e284dcebc3ad74eb519419b6c

Observation 7d992a44-ebc4-49d2-84e8-ccae3b12905f · inbound

FBQuant: FeedBack Quantization for Large Language Models cites this paper.

FBQuant: FeedBack Quantization for Large Language Models Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T14:44:36.238802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:44:36.238802Z digest=sha256:ba28ff4c630a087f70f35f0a32307c004c110e0c7c74052e781fa05449e22b72

Observation d563c240-c76a-4cc3-aba1-c10f28543947 · inbound

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives cites this paper.

Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-09T11:28:42.466468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:28:42.466468Z digest=sha256:d96e1dafa0be9fbdea048c27dd7fa103c0c6d5bcf443f359142510173536377b

Observation 7da6e152-8ad4-4cea-ac32-69c7dc5cf007 · inbound

ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations cites this paper.

ProcrustesGPT: Compressing LLMs with Structured Matrices and Orthogonal Transformations Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T11:20:43.149426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:20:43.149426Z digest=sha256:0c73fc063dc11704f7a76983e31adc8d8e2c99e613b1ce515bbeddeb95a088a6

Observation f7cc1034-a6d6-4036-bc85-fa35fd6a9907 · inbound

On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization cites this paper.

On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-06T18:07:17.680950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:07:17.680950Z digest=sha256:e74a4d0ebd8e3efa23a9cc7e6491bf32ca396cd061676b6d2bad8d17b8ed3644

Observation b24e3611-12d8-4704-a2db-70d60ead3a6b · inbound

On the transferability of Sparse Autoencoders for interpreting compressed models cites this paper.

On the transferability of Sparse Autoencoders for interpreting compressed models Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T15:24:45.783003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:24:45.783003Z digest=sha256:1527706575ea439880f11da83396aa223e787bc654df475b0c2184d46f1c76c9

Observation 3c9189af-1abb-46b4-a642-9bd527f4b9f1 · inbound

SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices cites this paper.

SigmaScale: LLM Compression with SVD-based Low-Rank Decomposition and Learned Scaling Matrices Compressing Large Language Models using Low Rank and Low Precision Decomposition

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-06-27T22:11:20.850073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T22:04:32.524875Z digest=sha256:e7fad3447ac911944db2f31a98b752175564e64beb7026042734f43c15f4788f