Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Data-free Weight Compress and Denoise for Large Language Models
As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.16319.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:21:05.872245Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T22:18:03.996099Z
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 5e8e2ad3-33a5-415d-bfb0-26c6632f2d6e · inbound
MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs cites this paper.
MGAA: Multi-Granular Adaptive Allocation fof Low-Rank Compression of LLMs Data-free Weight Compress and Denoise for Large Language Models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:21:05.872245Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9feef32-523d-41e2-8d48-216a813d3df6 · inbound
Compress Any Segment Anything Model (SAM) cites this paper.
Compress Any Segment Anything Model (SAM) Data-free Weight Compress and Denoise for Large Language Models
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:20:01.082405Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ec1d2a2-cfa1-4d9f-96bf-1027a2a35df6 · inbound
Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression cites this paper.
Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression Data-free Weight Compress and Denoise for Large Language Models
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T22:18:03.999999Z
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.