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Paper Citation Record · LEDGER

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2507.01806.

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

pith.paper-citation-record.v1
2507.01806 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:53:30.040384Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e524735-6763-44de-85c8-3fc4b97d08e1 · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:32.071309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.269447Z digest=sha256:6e18d69beabae96f158641a1defe02036421f0b6bfaeface9bd40ef50e2b6526

Observation 0bb92516-8d41-4492-83d5-c5268134d127 · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:31.853600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.350974Z digest=sha256:e47b695464bd379113ace1726ba1de6dd65838feb424f1f212ef234ee3887191

Observation 2a76d948-1307-4ca7-b022-c0dc7e660e54 · outbound

This paper cites Table 2 reports the time elapsed at each stage of our LoRA generation pipeline, measured on a Dell XPS15 (Intel i7-13700H, 14 cores, 64 GB RAM).

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Table 2 reports the time elapsed at each stage of our LoRA generation pipeline, measured on a Dell XPS15 (Intel i7-13700H, 14 cores, 64 GB RAM)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:53:31.617369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.429079Z digest=sha256:660188620b7f24a043928d847525e1c21c62122aad76f384305d0f128df6fb18

Observation 3ec061e2-af84-449a-8e14-65fd3695a15d · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:30.620387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.873779Z digest=sha256:6356d12d4fe24ffdc07eb81310e461465da28514fb7dce17e85c63bfa280e6f6

Observation 74803aef-1d6b-4b9d-8ed7-cceae4d72263 · outbound

This paper cites Expected Answer:.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Expected Answer:

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:53:30.366741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:30.040384Z digest=sha256:6c98dc66e8d583f7576f38ca91e5444d300afa37fa7e9a35d46bae3413747daf

Observation 5426550e-568e-484e-bcc5-132c9ecf6edb · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:32.661214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.001816Z digest=sha256:e0d0a66b6821f2500edc956801255430650dcc9779130f848f560f352f17fbde

Observation 3f1efa76-fa9b-43c9-ad2e-8aa4959e660e · outbound

This paper cites URL https: //doi.org/10.1007/978-3-030-56402-5.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs URL https: //doi.org/10.1007/978-3-030-56402-5

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:29.093799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:29.093799Z digest=sha256:9f4337b1b60279fba1d58b558e496ad21760403f094017baef0e1056fdbf0042

Observation 2c4ae8f2-ff1e-4c9e-b206-6e191f34e009 · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:31.334895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.522326Z digest=sha256:b66f5f8ece397d25f2303356a7b0d77ff071f2c20922d54ff85db6c6de852c9b

Observation 4f97af6a-aced-4721-99b9-8dd869d1cd25 · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:31.069823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.598399Z digest=sha256:2b0cdcb729bd491005496e24106d2db7d25939c886a309165e0023ec7d351ce7

Observation eec41203-6178-449d-bdc8-513b22a1982b · outbound

This paper cites an unresolved cited work.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-06T20:53:30.851551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.759056Z digest=sha256:c827c256d179c6854c14098a7271eda81c9a7545ede25583fe359ca2f91b5fee

Observation a9e8ba4a-892b-4025-ac4f-ef500716d49d · outbound

This paper cites A hitchhiker’s guide.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs A hitchhiker’s guide

Reference 2006

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:28.894826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:28.894826Z digest=sha256:8de2e6584a27c60d74ac5439e2ad0cc67e97f8302c6e92aa62205a41a95926aa

Observation 67e36b4f-4bfb-4796-94a9-3423ad939ee1 · outbound

This paper cites Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:28.445295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:28.445295Z digest=sha256:64c9fb9a8d87c1372211cb10a2b86aca2185ba2d05514608a2c4b53b190af50d

Observation d4af1f95-1c90-4b2e-8194-888929e98ca8 · outbound

This paper cites copy” of S in “distance domain.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs copy” of S in “distance domain

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:53:32.364385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:29.194089Z digest=sha256:8d5d45757e1a9f145981b11051b0e82a3c57e8f0ececc10737ac6b648b7e0e78

Observation 5d781889-c3e9-47a4-ad91-8cd4cc408c68 · outbound

This paper cites Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vuli´c, Sebastian Ruder, Kyunghyun Cho, and Iryna Gurevych.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vuli´c, Sebastian Ruder, Kyunghyun Cho, and Iryna Gurevych

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:53:32.928779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T20:53:28.342804Z digest=sha256:d589aaf48debfa5fa827397c5187469cbeb9f31d97ed8f5c793ce70830eb9acb

Observation 461fffb6-3e5d-4d2f-91ee-61c23dff2ad3 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs High-Resolution Image Synthesis with Latent Diffusion Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:28.617124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:28.617124Z digest=sha256:d9a48cd3fcd0fb4bb2cd92fff5c639b4f62360ac6991f2239383b8b2826208a3

Observation 7e44a120-e246-4620-b9dd-d876daa9179c · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs QLoRA: Efficient Finetuning of Quantized LLMs

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:28.773451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:28.773451Z digest=sha256:23b8159f3337922e2a48553ddfb78bb8d78e3030c3d0412db97183c7ddd296a0

Pith citing papers

No inbound Pith citation observations are available.