Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficient Post-training Quantization with FP8 Formats
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.14592.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:58:07.344437Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T19:43:54.661520Z
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 151eca64-8839-4a13-bc73-a709b13deba7 · inbound
Speeding up Model Loading with fastsafetensors cites this paper.
Speeding up Model Loading with fastsafetensors Efficient Post-training Quantization with FP8 Formats
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:58:07.344437Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a916cf99-c826-4b82-818e-6f263f7b25bf · inbound
PipeWeave: Synergizing Analytical and Learning Models for Unified GPU Performance Prediction cites this paper.
PipeWeave: Synergizing Analytical and Learning Models for Unified GPU Performance Prediction Efficient Post-training Quantization with FP8 Formats
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T12:47:54.056112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6e5347c0-77b4-4e35-afaa-018cabf024db · inbound
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models cites this paper.
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models Efficient Post-training Quantization with FP8 Formats
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:43:54.663079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.