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Paper Citation Record · LEDGER

Mirror Descent View for Neural Network Quantization

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.08237.

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

pith.paper-citation-record.v1
1910.08237 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:50:44.445400Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 d820d57e-b7f0-496e-9c06-52fa78ca6095 · inbound

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training cites this paper.

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training Mirror Descent View for Neural Network Quantization

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-04T08:50:44.445400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:50:44.445400Z digest=sha256:190cebcc75f72801de04af9a16ee78d041af934a325d3ab6be485611b3e6e201

Observation e5d08d8d-0c72-40e0-bb01-9db0a45e781d · inbound

Cross-Layer Error Compensation and Finite-Sample Feature-Statistics Matching for Extreme Low-Bit Quantization of Large Language Models cites this paper.

Cross-Layer Error Compensation and Finite-Sample Feature-Statistics Matching for Extreme Low-Bit Quantization of Large Language Models Mirror Descent View for Neural Network Quantization

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-02T01:35:43.747800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:35:43.747800Z digest=sha256:19fa8b3033f7f9c3570573ad545061702f222bfcd8310b455f3e99a40c5b5655