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Paper Citation Record · LEDGER

Learning low-precision neural networks without Straight-Through Estimator(STE)

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1903.01061.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1903.01061 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T03:42:06.542142Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

5
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3cbb8cb6-560e-444e-a8e6-84b2763a93a5 · inbound

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization cites this paper.

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization Learning low-precision neural networks without Straight-Through Estimator(STE)

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-23T22:28:31.082025Z

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.

source=pdf_text observed=2026-05-23T22:25:53.700079Z digest=sha256:cb6d3af95079d64a3b3c097ba680d279b2b57dce10f7bfec46c874832ba2c14c

Observation 62754cad-5810-4b47-840e-37c0fcd5aeb4 · inbound

Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks cites this paper.

Layerwise Progressive Freezing: A Training Scaffold for Depth-Scalable Binary Networks Learning low-precision neural networks without Straight-Through Estimator(STE)

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-06-29T05:13:06.560134Z

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.

source=arxiv_source observed=2026-06-29T05:08:23.176105Z digest=sha256:b28b715528a1597565cbe763920a870ed34d6d06773e8930f15d42796980d876

Observation 4caa36cb-11a4-4769-a094-fdc7dcfcac8d · inbound

Commissioning and Low Latency Operation of the Graph Neural Network Electromagnetic Calorimeter Trigger at the Belle II Experiment cites this paper.

Commissioning and Low Latency Operation of the Graph Neural Network Electromagnetic Calorimeter Trigger at the Belle II Experiment Learning low-precision neural networks without Straight-Through Estimator(STE)

Reference 35

Resolution
unresolved
no resolver link, observed 2026-07-13T03:42:06.542142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T03:42:06.542142Z digest=sha256:305b029010776dd87be793acad8f4ddfe913cb13f0c3a70b5510a7dd5a567c9c