Paper Citation Record · LEDGER

Sharpness-aware Quantization for Deep Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2111.12273.

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

pith.paper-citation-record.v1
2111.12273 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:04:02.956190Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:09:58.867803Z

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 c180ca09-9f15-48a2-b7ec-15c3a2e27e4e · inbound

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs cites this paper.

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs Sharpness-aware Quantization for Deep Neural Networks

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T05:04:02.956190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f253815f-cd98-4c19-96f9-76d3a609d259 · inbound

Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective cites this paper.

Quantization Meets OOD: Generalizable Quantization-aware Training from a Flatness Perspective Sharpness-aware Quantization for Deep Neural Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T13:12:23.898592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48df9c11-bbdf-4d7b-967d-965bad4f75b4 · inbound

Zero-Shot Quantization via Weight-Space Arithmetic cites this paper.

Zero-Shot Quantization via Weight-Space Arithmetic Sharpness-aware Quantization for Deep Neural Networks

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:08:12.585147Z

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 10c147cb-fb89-444d-824d-1442f4b35c77 · inbound

Certification of Machine Learning Models via Directional Sharpness cites this paper.

Certification of Machine Learning Models via Directional Sharpness Sharpness-aware Quantization for Deep Neural Networks

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:58.870303Z

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 180dffd3-73a0-4105-8ae1-07afd4cbc80e · inbound

Neural Network Quantization by Learning Low-Loss Subspaces cites this paper.

Neural Network Quantization by Learning Low-Loss Subspaces Sharpness-aware Quantization for Deep Neural Networks

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:59:58.379283Z

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.