Paper Citation Record · LEDGER

Neural Networks with Few Multiplications

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1510.03009.

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

pith.paper-citation-record.v1
1510.03009 v3

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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:42:07.765280Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T04:33:25.463013Z

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 64b08c3a-af58-45ea-8a7d-d61474f870f7 · inbound

HadamRNN: Binary and Sparse Ternary Orthogonal RNNs cites this paper.

HadamRNN: Binary and Sparse Ternary Orthogonal RNNs Neural Networks with Few Multiplications

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T10:42:07.765280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d0ed114-46a8-4c54-b7df-9ba1d5436ad0 · inbound

AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers cites this paper.

AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers Neural Networks with Few Multiplications

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T22:07:50.743973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa3db861-59ee-4c77-8468-6f861c36ff60 · inbound

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization cites this paper.

Exploring Model Invariance with Discrete Search for Ultra-Low-Bit Quantization Neural Networks with Few Multiplications

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T22:37:02.530378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a92f3c46-4640-49d0-8002-28fc28e46dbe · inbound

BiVM: Accurate Binarized Neural Network for Efficient Video Matting cites this paper.

BiVM: Accurate Binarized Neural Network for Efficient Video Matting Neural Networks with Few Multiplications

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T19:54:31.680996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35d92e92-14f5-43cf-81d1-3caacc407407 · inbound

Neutralizing Token Aggregation via Information Augmentation for Efficient Test-Time Adaptation cites this paper.

Neutralizing Token Aggregation via Information Augmentation for Efficient Test-Time Adaptation Neural Networks with Few Multiplications

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-06T04:33:25.561179Z

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.