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Paper Citation Record · LEDGER

Crafting Efficient Fine-Tuning Strategies for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.13906.

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

pith.paper-citation-record.v1
2407.13906 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 2026-08-08T19:48:54.244910Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T00:33:52.643474Z

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 600ed0c1-0186-4e06-842a-c7b7645e9312 · inbound

Fine-Tuned LLMs are "Time Capsules" for Tracking Societal Bias Through Books cites this paper.

Fine-Tuned LLMs are "Time Capsules" for Tracking Societal Bias Through Books Crafting Efficient Fine-Tuning Strategies for Large Language Models

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-08T19:48:54.244910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T19:48:54.244910Z digest=sha256:645fc2f17c2ed62ebc77245f70f34d0ad4e8d894adaa09a44d9aa8d3892be652

Observation 9a072582-b58d-4136-9c7e-f42cfa4bb489 · inbound

A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search cites this paper.

A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search Crafting Efficient Fine-Tuning Strategies for Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-03T09:45:43.735716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:45:43.735716Z digest=sha256:60e86875f1805be85cfe59cd6bf1e411917c994810dc6c4d296db9aecaf5402e

Observation a3dcc804-41bb-41f5-9f74-8370d6853b9a · inbound

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective cites this paper.

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective Crafting Efficient Fine-Tuning Strategies for Large Language Models

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:46:12.481875Z

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.

source=arxiv_source observed=2026-05-08T08:06:25.436395Z digest=sha256:d9eff33ed929025f91ad3f3b07132e690f5a769d7edf855df398289feeca9a2e

Observation 332bbcc2-47c4-43d7-a69e-3c00898df5ac · inbound

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective cites this paper.

Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective Crafting Efficient Fine-Tuning Strategies for Large Language Models

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-21T00:33:52.645114Z

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.

source=arxiv_source observed=2026-05-21T00:33:22.181383Z digest=sha256:12e0d9e9afee474d7db484c9e34f6e4ae65a0a8dde8dc4dbcb165d7942c5be8c