Paper Citation Record · LEDGER

What Matters In The Structured Pruning of Generative Language Models?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2302.03773.

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

pith.paper-citation-record.v1
2302.03773 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:30:09.199585Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:36:55.152927Z

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 f9bb6cca-ea5f-462f-b87e-a3b640c22764 · inbound

TinyStories: How Small Can Language Models Be and Still Speak Coherent English? cites this paper.

TinyStories: How Small Can Language Models Be and Still Speak Coherent English? What Matters In The Structured Pruning of Generative Language Models?

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:36:55.156637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6d9f93b3-8059-4263-909e-d1bfdeedb72a · inbound

Data Pruning in Generative Diffusion Models cites this paper.

Data Pruning in Generative Diffusion Models What Matters In The Structured Pruning of Generative Language Models?

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T17:30:09.199585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de793964-36c6-4955-a4d1-a7c08505a15c · inbound

AutoMixQ: Self-Adjusting Quantization for High Performance Memory-Efficient Fine-Tuning cites this paper.

AutoMixQ: Self-Adjusting Quantization for High Performance Memory-Efficient Fine-Tuning What Matters In The Structured Pruning of Generative Language Models?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:35.756424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 352fd51b-03cb-45a0-85ce-1bfc6dd05e0a · inbound

CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models cites this paper.

CPTQuant - A Novel Mixed Precision Post-Training Quantization Techniques for Large Language Models What Matters In The Structured Pruning of Generative Language Models?

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T23:50:28.928546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c5ecd07-9238-4c85-abee-69d1fbf043e6 · inbound

QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models cites this paper.

QPruner: Probabilistic Decision Quantization for Structured Pruning in Large Language Models What Matters In The Structured Pruning of Generative Language Models?

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T14:48:56.329715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b759b7-c049-45ed-b124-21e351c3c0c9 · inbound

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference cites this paper.

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference What Matters In The Structured Pruning of Generative Language Models?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T11:12:57.923654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44967318-9bc6-4813-a3a1-b68448dcf17e · inbound

On Accelerating Edge AI: Optimizing Resource-Constrained Environments cites this paper.

On Accelerating Edge AI: Optimizing Resource-Constrained Environments What Matters In The Structured Pruning of Generative Language Models?

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T14:46:38.321953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f61c9a06-f5c9-452c-b827-fb2832b42f46 · inbound

SwiftPrune: Hessian-Free Weight Pruning for Large Language Models cites this paper.

SwiftPrune: Hessian-Free Weight Pruning for Large Language Models What Matters In The Structured Pruning of Generative Language Models?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T15:21:23.570687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80007b7f-b52a-4a6f-8321-32203d1285be · inbound

Post-Training Neural Network Pruning using Graph Curvature cites this paper.

Post-Training Neural Network Pruning using Graph Curvature What Matters In The Structured Pruning of Generative Language Models?

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T08:45:16.488503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.