Paper Citation Record · LEDGER

Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:1609.07061.

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

pith.paper-citation-record.v1
1609.07061 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:57:54.355880Z

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

1425
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2927e1ac-948d-4c86-b4c5-705189225048 · inbound

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications cites this paper.

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T02:50:40.305343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c8008e1c-343e-4a5a-a9c0-7e557a4c2420 · inbound

Mixed Precision Training cites this paper.

Mixed Precision Training Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:47:18.487769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a088b7c4-4a45-457d-81ee-21916419d794 · inbound

New pointwise convolution in Deep Neural Networks through Extremely Fast and Non Parametric Transforms cites this paper.

New pointwise convolution in Deep Neural Networks through Extremely Fast and Non Parametric Transforms Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-25T16:56:04.223594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f42592a-3bc7-4d45-b1f4-b561b0858ea7 · inbound

EPNAS: Efficient Progressive Neural Architecture Search cites this paper.

EPNAS: Efficient Progressive Neural Architecture Search Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-25T01:16:31.729807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a6088260-eb03-481f-85e8-37891d31882e · inbound

Fast Inference from Transformers via Speculative Decoding cites this paper.

Fast Inference from Transformers via Speculative Decoding Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-17T22:52:00.149105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 243fb917-ee67-446c-b2b1-6edba1a2a6be · inbound

A Discrepancy-Based Perspective on Dataset Condensation cites this paper.

A Discrepancy-Based Perspective on Dataset Condensation Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T17:57:54.355880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a1c2500-c551-42b9-8ff2-3780de76e3fc · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:06:27.874626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd85d3f2-a0e2-4914-94b4-e413ea4ac591 · inbound

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-15T04:59:46.157213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b982565f-d86a-4ef5-bec1-a8602af04148 · inbound

A Geometric Analysis of Sign-Magnitude Asymmetry in a ReLU + RMSNorm Block under Ternary Quantization cites this paper.

A Geometric Analysis of Sign-Magnitude Asymmetry in a ReLU + RMSNorm Block under Ternary Quantization Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T13:08:17.794531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6a55fdd6-ae4b-447d-b0cc-55f6c8106252 · 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 Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-06-29T05:13:06.499241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5abe070d-6ecb-48ec-9ad8-cacbec2843f0 · inbound

Recti-Q: Feature-Space Rectification for Out-of-Distribution-Robust Quantized Perception in Edge Robotics cites this paper.

Recti-Q: Feature-Space Rectification for Out-of-Distribution-Robust Quantized Perception in Edge Robotics Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T15:11:09.153754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.