Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.10975.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T05:04:32.514562Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T21:06:14.392580Z
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 87208147-9d27-43ac-a98e-2add23867634 · inbound
Unified Stochastic Framework for Neural Network Quantization and Pruning cites this paper.
Unified Stochastic Framework for Neural Network Quantization and Pruning SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:04:32.514562Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9aaf2a48-5299-41fe-9163-4c6a1500b0b8 · inbound
Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos cites this paper.
Provable Post-Training Quantization: Theoretical Analysis of OPTQ and Qronos SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T23:52:53.096038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 569dfc30-78b2-41b3-9cc7-5e8c752ff1d5 · inbound
GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation cites this paper.
GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation SPFQ: A Stochastic Algorithm and Its Error Analysis for Neural Network Quantization
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T21:06:14.393820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.