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Paper Citation Record · LEDGER

SingLoRA: Low Rank Adaptation Using a Single Matrix

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2507.05566.

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

pith.paper-citation-record.v1
2507.05566 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:38:17.656155Z

measured 23 of 23 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 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

23 of 23 outbound references displayed

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  • verified fuzzy9
  • unresolved14
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e91990ab-8c47-412a-b001-1afada1478a8 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

SingLoRA: Low Rank Adaptation Using a Single Matrix Emerging properties in self-supervised vision transformers

Reference 1

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source=pdf_text observed=2026-08-06T19:38:15.099042Z digest=sha256:dd226614f8d3393228360a7d59865d3c019f08a9ef663c324259bcfd5cd77262

Observation 04c39996-c1ae-47ab-9ab1-46d659f0e05b · outbound

This paper cites KronA: Parameter Efficient Tuning with Kronecker Adapter.

SingLoRA: Low Rank Adaptation Using a Single Matrix KronA: Parameter Efficient Tuning with Kronecker Adapter

Reference 2

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source=pdf_text observed=2026-08-06T19:38:15.155839Z digest=sha256:186c1a8276090847be6e452eeddb39a19714c81b5e289bc477b154ce56fb1d99

Observation 2a466616-e921-4703-b301-bad21c3ff9fa · outbound

This paper cites On the impact of the activation function on deep neural networks training.

SingLoRA: Low Rank Adaptation Using a Single Matrix On the impact of the activation function on deep neural networks training

Reference 3

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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=2026-08-06T19:38:15.262585Z digest=sha256:e615a96ed704e63f734504787b13f219ce8c6463695f2a8d1db6ef4d829195a4

Observation 16ac998f-462d-42bc-b382-a8e1857f49e4 · outbound

This paper cites Lora+: Efficient low rank adaptation of large models.

SingLoRA: Low Rank Adaptation Using a Single Matrix Lora+: Efficient low rank adaptation of large models

Reference 4

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:38:15.359502Z digest=sha256:95400064c86351d1bd7b8357870826923a387d2308cfc0ac3e2f6f8e72373bfc

Observation b65026d6-c069-4621-b7eb-532bce592035 · outbound

This paper cites Deep residual learning for image recognition.

SingLoRA: Low Rank Adaptation Using a Single Matrix Deep residual learning for image recognition

Reference 5

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source=pdf_text observed=2026-08-06T19:38:15.475371Z digest=sha256:5209835b4234bbe24ca4ebffd79ae67325ff742107575fce47c36fa704345dbe

Observation 654c66e8-b4a4-417d-a9f1-f56e3537b8c2 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

SingLoRA: Low Rank Adaptation Using a Single Matrix LoRA: Low-Rank Adaptation of Large Language Models

Reference 6

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source=pdf_text observed=2026-08-06T19:38:15.570435Z digest=sha256:603b9b2f31e642b3f40e5d3050a2e25d3cba57394337e6415aef645f56c21194

Observation 999515d1-e927-4982-bfc8-5d796c9df1da · outbound

This paper cites Fedpara: Low-rank hadamard prod- uct for communication-efficient federated learning.

SingLoRA: Low Rank Adaptation Using a Single Matrix Fedpara: Low-rank hadamard prod- uct for communication-efficient federated learning

Reference 7

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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=2026-08-06T19:38:15.606560Z digest=sha256:6cdff5c51d2170a6dd564f2dc315d7fd959461499d1ff956636f6e19c2f55134

Observation 80e797d9-0712-4b25-b347-401a247da552 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

SingLoRA: Low Rank Adaptation Using a Single Matrix Adam: A Method for Stochastic Optimization

Reference 8

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source=pdf_text observed=2026-08-06T19:38:15.667118Z digest=sha256:deafaf73d8230b608cdb1c5c45eda635127acbacbf2bdfc5bbbabe83634d6017

Observation 5a63b2cd-7401-4ff0-a329-6a8d48669534 · outbound

This paper cites Dora: Weight-decomposed low-rank adaptation.

SingLoRA: Low Rank Adaptation Using a Single Matrix Dora: Weight-decomposed low-rank adaptation

Reference 9

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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=2026-08-06T19:38:15.762515Z digest=sha256:2f59264912a7269b30ec0c163f09849a3450f4b5dfd1255111a4629a42ad7bec

Observation 798b9c33-030c-465d-bc25-0295a405d115 · outbound

This paper cites Learning transferable visual models from natural language supervision.

SingLoRA: Low Rank Adaptation Using a Single Matrix Learning transferable visual models from natural language supervision

Reference 10

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source=pdf_text observed=2026-08-06T19:38:15.898601Z digest=sha256:a8551bfa50d8151cda7106a5af4a7e04e056ab0bd275c3e19e5137afb8fddcf4

Observation 465d10b7-db44-4325-bd12-25516ce23f70 · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

SingLoRA: Low Rank Adaptation Using a Single Matrix High- resolution image synthesis with latent diffusion models

Reference 11

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source=pdf_text observed=2026-08-06T19:38:15.993443Z digest=sha256:40862b031b579f667ba01af518f21f27eaeca9da7812e4b1ef99abf10548cc6d

Observation fe034c92-bc37-4cba-9699-ef3dc9e7b217 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

SingLoRA: Low Rank Adaptation Using a Single Matrix Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 12

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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=2026-08-06T19:38:16.182688Z digest=sha256:0fec6e58b14b99eca43c862725dc9de5d604667f1b8bec88fd4cd951340eb152

Observation becde22c-1635-472e-aab0-be941aa1c06f · outbound

This paper cites Deep Information Propagation.

SingLoRA: Low Rank Adaptation Using a Single Matrix Deep Information Propagation

Reference 13

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source=pdf_text observed=2026-08-06T19:38:16.313257Z digest=sha256:288f72e34e783f038431e1eed1887fbf9d0fae2845afd56e04a31ff5603bd61d

Observation d3ed0767-954a-4c1c-985d-f3878aeb33a4 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

SingLoRA: Low Rank Adaptation Using a Single Matrix LLaMA: Open and Efficient Foundation Language Models

Reference 14

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source=pdf_text observed=2026-08-06T19:38:16.414483Z digest=sha256:d71afc93ae34e1b4445d079ee0aa0f556470302f39f9f1bd753e74e6f3ef475c

Observation aada361a-1209-4dc6-bbc8-47ec75cb8ed5 · outbound

This paper cites Dylora: Parameter efficient tuning of pre-trained models using dynamic search-free low-rank adaptation.

SingLoRA: Low Rank Adaptation Using a Single Matrix Dylora: Parameter efficient tuning of pre-trained models using dynamic search-free low-rank adaptation

Reference 15

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raw_fallback, observed 2026-08-06T19:38:18.737377Z

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=2026-08-06T19:38:16.542796Z digest=sha256:ace7582945f6e9bd54a562d23c9272d28fd34f43e0da457ffddb2e81a213c2f0

Observation 44ccaeea-198f-44a7-9096-2916006e0f17 · outbound

This paper cites Glue: A multi-task benchmark and analysis platform for natural language under- standing.

SingLoRA: Low Rank Adaptation Using a Single Matrix Glue: A multi-task benchmark and analysis platform for natural language under- standing

Reference 16

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raw_fallback, observed 2026-08-06T19:38:18.536881Z

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=2026-08-06T19:38:16.639007Z digest=sha256:9a879214ae56c59910e566cea4cf223c7c22670d23d25a720eaf93d393dd72a7

Observation a9fd95c1-acac-4044-b814-f73f22274a83 · outbound

This paper cites Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer.

SingLoRA: Low Rank Adaptation Using a Single Matrix Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Reference 17

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source=pdf_text observed=2026-08-06T19:38:16.774558Z digest=sha256:1740b344d819e2ac4b4920774868e4dfd57719ffdbc12b96fc43599400dba1c2

Observation 902f8844-e176-4fce-ad62-704af23d6f40 · outbound

This paper cites Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks.

SingLoRA: Low Rank Adaptation Using a Single Matrix Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks

Reference 18

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source=pdf_text observed=2026-08-06T19:38:16.960316Z digest=sha256:3cb6887d7e9064323bb1988171762fe30e2d8da41b921fa55c5b13778ed2d8ce

Observation 3cf8c25d-b2ba-4075-a0af-6040319857db · outbound

This paper cites Lora done rite: Robust invariant transformation equilibration for lora optimization.

SingLoRA: Low Rank Adaptation Using a Single Matrix Lora done rite: Robust invariant transformation equilibration for lora optimization

Reference 19

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raw_fallback, observed 2026-08-06T19:38:18.274900Z

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=2026-08-06T19:38:17.054553Z digest=sha256:12b5cd959061b3aa21502a1f1f07fd518d43ba12f24258a9317f399c8642f434

Observation 14d0e14a-b491-4839-8a4f-e0fa816ac1e1 · outbound

This paper cites Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models.

SingLoRA: Low Rank Adaptation Using a Single Matrix Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models

Reference 20

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source=pdf_text observed=2026-08-06T19:38:17.133482Z digest=sha256:94c828aeb5c5404a2ad34f5c3b28fc2afe8e507bac214cb178f967e6627a9b5f

Observation a71d0fbc-dfcf-440e-8a9f-79f6ad266781 · outbound

This paper cites Adalora: Adaptive budget allocation for parameter- efficient fine-tuning.

SingLoRA: Low Rank Adaptation Using a Single Matrix Adalora: Adaptive budget allocation for parameter- efficient fine-tuning

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-06T19:38:18.005788Z

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=2026-08-06T19:38:17.275447Z digest=sha256:6bdef3b5f78b406dd05caea97dec3d3b5f03cd6be9e04f1a57d85d14962fc406

Observation 1e311720-137b-4784-b3f1-52d732647a88 · outbound

This paper cites LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation.

SingLoRA: Low Rank Adaptation Using a Single Matrix LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation

Reference 22

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source=pdf_text observed=2026-08-06T19:38:17.491829Z digest=sha256:32ab634605683d86d3d23792d04bb0c3f7622234ee2b0eb6226d4b040b7c290c

Observation a329e872-e948-4d14-9fd5-7fb543b8c378 · outbound

This paper cites Delta-LoRA: Fine-Tuning High-Rank Parameters with the Delta of Low-Rank Matrices.

SingLoRA: Low Rank Adaptation Using a Single Matrix Delta-LoRA: Fine-Tuning High-Rank Parameters with the Delta of Low-Rank Matrices

Reference 23

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source=pdf_text observed=2026-08-06T19:38:17.656155Z digest=sha256:3c9781c11b10336081f26dede13a45f491e3c353bf4ca53f1c632c15c1be7262

Pith citing papers

No inbound Pith citation observations are available.