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Paper Citation Record · LEDGER

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2602.04998.

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

pith.paper-citation-record.v1
2602.04998 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:37:27.957110Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T14:08:21.901987Z

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 baad59e7-3ae2-4ee3-9e25-1e74354d4a1f · inbound

CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation with Non-linearity Retained at Inference cites this paper.

CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation with Non-linearity Retained at Inference Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T02:04:51.678500Z

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.

source=pdf_text observed=2026-05-15T18:55:02.067855Z digest=sha256:95b7bbe26e9b4db9eda6be7e03e9673f1a55931d5a65013f0f2794cc7831f2c1

Observation cd955bd4-0fb0-49ce-99df-314e580067f2 · inbound

CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation with Non-linearity Retained at Inference cites this paper.

CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation with Non-linearity Retained at Inference Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-02T20:37:27.957110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:37:27.957110Z digest=sha256:3ba16826e9a8f1eb928b82283cddf1c3552c75b1add4e6c76a89b605929456ba

Observation dcb6b5d9-9f97-442e-917e-8c32da8fce70 · inbound

The Hidden Power of Scaling Factor in LoRA Optimization cites this paper.

The Hidden Power of Scaling Factor in LoRA Optimization Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Reference 131

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T14:08:21.903465Z

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.

source=arxiv_source observed=2026-06-27T07:14:08.479610Z digest=sha256:86509a2a04bfd7fc69747ecfb7f9074e7b17dc65b655137c5f1877755852a982

Observation 4a83669e-bd95-4d7a-bf67-c65b80da2199 · inbound

Scaling Point-in-Time Language Models cites this paper.

Scaling Point-in-Time Language Models Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-02T15:39:38.407161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:39:38.407161Z digest=sha256:16f1bf566b8a30e79f7d65afe0ecccf55e49355397f7febaa82719fa1eb56b95

Observation afb31c7d-84aa-4028-893a-3f5a1f372c10 · inbound

Between Gradient and Natural Gradient: A Continuum of LoRA Initializations cites this paper.

Between Gradient and Natural Gradient: A Continuum of LoRA Initializations Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T00:26:40.999766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T00:26:40.999766Z digest=sha256:e2f87bdeb8f734c14da7a7a498e579c9fdfea48e39954f69b7fc0b7cbb5d2f84