Paper Citation Record · LEDGER

Pruning vs Quantization: Which is Better?

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2307.02973.

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

pith.paper-citation-record.v1
2307.02973 v2

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:45:20.895622Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T21:16:34.320413Z

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 356d8c24-6cbb-443d-9edf-c376709b10f4 · inbound

UPAQ: A Framework for Real-Time and Energy-Efficient 3D Object Detection in Autonomous Vehicles cites this paper.

UPAQ: A Framework for Real-Time and Energy-Efficient 3D Object Detection in Autonomous Vehicles Pruning vs Quantization: Which is Better?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T21:45:20.895622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98fdc05b-6867-4948-aa1b-7f776600a02a · inbound

Information-Bottleneck Driven Binary Neural Network for Change Detection cites this paper.

Information-Bottleneck Driven Binary Neural Network for Change Detection Pruning vs Quantization: Which is Better?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T20:15:24.406351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d2c7a5f-74bd-4e8d-b462-927597d79998 · inbound

Explaining How Quantization Disparately Skews a Model cites this paper.

Explaining How Quantization Disparately Skews a Model Pruning vs Quantization: Which is Better?

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T22:41:17.422775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaae707c-ceb2-4163-ad59-77df1e7386f3 · inbound

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models cites this paper.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models Pruning vs Quantization: Which is Better?

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:47:08.839632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf225352-9c9e-41bd-9e9e-eba8b5bb9f1b · inbound

Voltron: Enabling Elastic Multi-Device Execution of LLM Inference for Empowered Edge Intelligence cites this paper.

Voltron: Enabling Elastic Multi-Device Execution of LLM Inference for Empowered Edge Intelligence Pruning vs Quantization: Which is Better?

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:16:34.321735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.