Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DeltaDQ: Ultra-High Delta Compression for Fine-Tuned LLMs via Group-wise Dropout and Separate Quantization
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.08666.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:56:48.406207Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T07:06:43.689219Z
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 6830f65a-a249-4be7-b46a-7bb74deda9cf · inbound
Dynamic Base model Shift for Delta Compression cites this paper.
Dynamic Base model Shift for Delta Compression DeltaDQ: Ultra-High Delta Compression for Fine-Tuned LLMs via Group-wise Dropout and Separate Quantization
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:56:48.406207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2062db1f-147c-4f8b-ab51-56dc08119b2b · inbound
STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models cites this paper.
STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models DeltaDQ: Ultra-High Delta Compression for Fine-Tuned LLMs via Group-wise Dropout and Separate Quantization
Reference 144
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T07:06:43.691444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.