Paper Citation Record · LEDGER

LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2305.18403.

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

pith.paper-citation-record.v1
2305.18403 v5

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 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:03:50.150580Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T07:16:04.188505Z

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 eece8467-a940-4d30-9a3e-59c99bc509f4 · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-13T11:32:37.137631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 35410915-288d-4501-a21e-73da44c434a7 · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 169

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:05:16.475146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3faaae99-1b2a-4eff-a91b-0fd3632e2971 · inbound

RAP: Runtime Adaptive Pruning for LLM Inference cites this paper.

RAP: Runtime Adaptive Pruning for LLM Inference LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:21:35.600815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 387bde6f-6707-497d-bb2a-e26386318834 · inbound

Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs cites this paper.

Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:03:50.150580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f917454-8130-4c47-9291-100440aea80f · inbound

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation cites this paper.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:43.815649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc6e8ff4-2f01-4fdd-98d8-d4f976dffa28 · inbound

SlimLLM: Accurate Structured Pruning for Large Language Models cites this paper.

SlimLLM: Accurate Structured Pruning for Large Language Models LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:30:21.169863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d46116-a700-4821-9c58-317345c79fdf · inbound

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs cites this paper.

MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:02:14.375780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 97d3112d-fc35-4633-8d29-ea6e107af233 · inbound

GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation cites this paper.

GradMAP: Faster Layer Pruning with Gradient Metric and Projection Compensation LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-02T23:12:07.547170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 998a433b-3a50-4272-b9a8-eb960f3ff038 · inbound

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation cites this paper.

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:06:14.414209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 400c6307-dab2-4c98-9956-0c8bfff0d564 · inbound

PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning cites this paper.

PALS: Percentile-Aware Layerwise Sparsity for LLM Pruning LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-07-09T07:16:04.191634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 72c9aa9b-2a55-434a-8003-4f91bdf4d635 · inbound

Constraint-Driven Model Optimization: An Industry Framework for Selecting Compression and Acceleration Techniques in Modern Machine Learning Systems cites this paper.

Constraint-Driven Model Optimization: An Industry Framework for Selecting Compression and Acceleration Techniques in Modern Machine Learning Systems LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T03:55:41.247033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.