Paper Citation Record · LEDGER

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1909.13144.

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

pith.paper-citation-record.v1
1909.13144 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:16:58.477426Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:58.367181Z

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 bb72d958-b350-44ae-8251-b31d9ad06b82 · inbound

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization cites this paper.

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:52:23.040497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 502681ad-5ac3-4bc8-b17d-82b1fb507a91 · inbound

Progressive Element-wise Gradient Estimation for Neural Network Quantization cites this paper.

Progressive Element-wise Gradient Estimation for Neural Network Quantization Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T15:16:58.477426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6befa921-d68b-48f0-9897-5ed1112ed01a · inbound

Integrating Pruning with Quantization for Efficient Deep Neural Networks Compression cites this paper.

Integrating Pruning with Quantization for Efficient Deep Neural Networks Compression Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T10:19:04.109703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3290b408-9e7d-4521-8bb7-de67f77074fd · inbound

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators cites this paper.

GRAU: Generic Reconfigurable Activation Unit Design for Neural Network Hardware Accelerators Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:47:51.784991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac391840-528e-4615-93d2-897c593990b8 · inbound

ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization cites this paper.

ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:55:31.975251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b91a1e9b-dc8b-40ba-8108-bd4302334a38 · inbound

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

Neural Network Quantization by Learning Low-Loss Subspaces Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T16:59:58.369177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 40571b96-b2d3-4235-add3-ac10a5b80388 · inbound

DSTAR: Accelerating Diffusion Transformers via Spatial and Temporal Redundancy Reduction cites this paper.

DSTAR: Accelerating Diffusion Transformers via Spatial and Temporal Redundancy Reduction Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T22:14:35.314045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.