Paper Citation Record · LEDGER

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.07461.

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

pith.paper-citation-record.v1
2410.07461 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:52:43.445537Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:13:14.029827Z

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 b7b3971b-1360-49f3-8fd6-00c87a768ecf · inbound

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning cites this paper.

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:13:14.033346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 34524cef-9230-4287-9642-fe97d20bba2d · inbound

Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs cites this paper.

Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T16:52:43.445537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d183cf41-3dc1-42e7-8892-6e3b2dc352a3 · inbound

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction cites this paper.

Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:51:33.780470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 59428d1a-2e8a-4a17-8538-2a4e173ef752 · inbound

Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization cites this paper.

Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T10:39:56.790507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.