Paper Citation Record · LEDGER

The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.04497.

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

pith.paper-citation-record.v1
2402.04497 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 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:50.649122Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T21:42:10.052466Z

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 9e004e3e-26da-4f68-86b0-7cae55897b15 · inbound

Quantum Adaptive Self-Attention for Quantum Transformer Models cites this paper.

Quantum Adaptive Self-Attention for Quantum Transformer Models The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:42:10.055544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 636e0c95-4aee-498a-ae0c-ceeb56d11482 · inbound

Subquadratic Algorithms and Hardness for Attention with Any Temperature cites this paper.

Subquadratic Algorithms and Hardness for Attention with Any Temperature The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.649122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 401772d2-ad91-4c1b-82a0-9e5a72015bd3 · inbound

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed cites this paper.

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:06:15.579083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a8423d9-9ba1-4bb4-b8a8-2e9fe79c97d5 · inbound

Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law The Fine-Grained Complexity of Gradient Computation for Training Large Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T14:02:56.619693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.