Paper Citation Record · LEDGER

HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1905.03696.

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

pith.paper-citation-record.v1
1905.03696 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:19:53.305424Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:54:21.739013Z

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 ae365b72-0a84-46af-82ae-9dbff7f0cef2 · inbound

Efficient Deep Neural Networks cites this paper.

Efficient Deep Neural Networks HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T12:19:53.305424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f542d025-43d7-4432-9b7f-338030262a83 · inbound

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling cites this paper.

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:11:46.553027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 62b25332-1dc6-487d-9c98-529a9f2dd1dd · inbound

Characterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and Localization cites this paper.

Characterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and Localization HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:54:21.740817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f45dc4b4-e35c-4d53-9dbc-029e2a64a2fc · inbound

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs cites this paper.

Recurrent Residual Quantization: A Progressive Multi-Precision Representation for LLMs HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T00:50:44.549499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.