Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Compressing Large Language Models using Low Rank and Low Precision Decomposition
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.18886.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:28:42.466468Z
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 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.
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.
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.
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.
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 2026-08-09T06:31:02.800959+00:00.