Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.04744.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:46:42.859488Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
2
pith, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 02d71e93-905a-4b71-974c-470125c9f663 · inbound
TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ee1ac38-5aff-4d23-8c93-c5580fb91aad · inbound
Efficient Column-Wise N:M Pruning on RISC-V CPU Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0798e960-4843-403a-afec-510fafde30f7 · inbound
MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Reference 91
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 30bf6e20-884a-4b73-b9c5-39b82b2665a9 · inbound
DeVIT: Low-Power Vision Transformer Acceleration Using Delta Computation Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.