Paper Citation Record · LEDGER

LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.10933.

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

pith.paper-citation-record.v1
2404.10933 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 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:57:52.375078Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T20:30:17.932573Z

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 73df6e8a-7fa8-4baf-910f-33d09488f446 · inbound

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO cites this paper.

A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:52.375078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f64185e-707c-443d-9d4f-045ae7e83c44 · inbound

GPU Memory and Utilization Estimation for Training-Aware Resource Management: Opportunities and Limitations cites this paper.

GPU Memory and Utilization Estimation for Training-Aware Resource Management: Opportunities and Limitations LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:30:17.936459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d04d764-7919-4418-8130-6cdb4e40c9f0 · inbound

CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification cites this paper.

CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:56:30.628715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d074fb79-dc6c-4115-8b90-a454deada706 · inbound

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators cites this paper.

FastTPS: An Optimized Method for LLM Token Phase for AI accelerators LLMem: Estimating GPU Memory Usage for Fine-Tuning Pre-Trained LLMs

Reference 42

Resolution: unresolved; no resolver link, observed 2026-07-14T06:16:09.070414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.