Paper Citation Record · LEDGER

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models

As of 14 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2412.20891.

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

pith.paper-citation-record.v1
2412.20891 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:12:34.618018Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:18:13.965082Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:18:18.087254Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy6
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b823c733-3439-4995-86bc-53c05c0fef9a · outbound

This paper cites LoTR: Low Tensor Rank Weight Adaptation.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LoTR: Low Tensor Rank Weight Adaptation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.470007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01a2a402-287b-461d-a683-06433656868c · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models On the Opportunities and Risks of Foundation Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.475835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74fcf5ea-b971-42e8-82b5-94659cdeac33 · outbound

This paper cites arXiv preprint arXiv:2406.00132 (2024).

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models arXiv preprint arXiv:2406.00132 (2024)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.481957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95e748cc-c849-4cbc-9e50-75c79c2232ef · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.487633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f860331-dd04-4b13-94c1-2a5f254ebdc9 · outbound

This paper cites SIAM Journal on Matrix Analysis and Applications 30(3), 1084–1127 (2008).

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models SIAM Journal on Matrix Analysis and Applications 30(3), 1084–1127 (2008)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.131153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 75e1243c-d69e-4095-9885-49e4512f8e20 · outbound

This paper cites Advances in Neural Information Processing Systems 36 (2024).

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Advances in Neural Information Processing Systems 36 (2024)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.116225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 25ee267b-71a9-4a46-9bac-c8d3800b2855 · outbound

This paper cites In: Burstein, J., Doran, C., Solorio, T.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models In: Burstein, J., Doran, C., Solorio, T

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.100398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c6343ddc-8b9a-468e-9eb7-73a299dc9514 · outbound

This paper cites The Llama 3 Herd of Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models The Llama 3 Herd of Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.507307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c404318-ac22-4281-a8d5-256f72117ce7 · outbound

This paper cites Physical Review Research 2(2), 023300 (2020).

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Physical Review Research 2(2), 023300 (2020)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.084587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 64f760a0-0fb3-4287-bafd-d5583e36d8cc · outbound

This paper cites In: Arai, K.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models In: Arai, K

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.069127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4f35b5f9-ccec-421d-85a8-fd7cf0eaf0a2 · outbound

This paper cites LoRA+: Efficient Low Rank Adaptation of Large Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LoRA+: Efficient Low Rank Adaptation of Large Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.522527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 216b64a9-2b31-4de0-a683-e104a3a0b44b · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.527904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c61dbe9a-b54e-42ed-8c15-937fb161b82d · outbound

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

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.533019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 328ab596-0432-4ed3-a814-c8c798ad3379 · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.537736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b1bb1db-bde9-473b-a941-7ddf6ffcd038 · outbound

This paper cites EdgeLLM: A Highly Efficient CPU-FPGA Heterogeneous Edge Accelerator for Large Language Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models EdgeLLM: A Highly Efficient CPU-FPGA Heterogeneous Edge Accelerator for Large Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.542323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 902a9b9d-04ce-4c15-ac90-790d8bb322c1 · outbound

This paper cites A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.546966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50a62c87-fb10-4f45-94c4-79d18128ade1 · outbound

This paper cites Measuring the Intrinsic Dimension of Objective Landscapes.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Measuring the Intrinsic Dimension of Objective Landscapes

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.555520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d00faf4d-d04a-4b49-abc3-deb9cd792a98 · outbound

This paper cites DoRA: Weight-Decomposed Low-Rank Adaptation.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.561026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cebeb8b4-9a9f-43db-b1d4-9454945a298b · outbound

This paper cites PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.565676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb48d9d9-bf1b-459b-862c-086ed0e5b8f0 · outbound

This paper cites New Journal of Physics 12(2), 025012 (2010).

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models New Journal of Physics 12(2), 025012 (2010)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:12:35.053708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 083707c7-711d-4f45-b87a-5e0fc4e79300 · outbound

This paper cites Compute Better Spent: Replacing Dense Layers with Structured Matrices.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Compute Better Spent: Replacing Dense Layers with Structured Matrices

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.574522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2df09d4-ff1d-44f7-9664-bf588d1abcd2 · outbound

This paper cites an unresolved cited work.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:12:35.038874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a4542c5-6aad-4a5f-b18e-34a343c9297f · outbound

This paper cites Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.583585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f415a5a-0be6-486b-94cc-17f42015bd2c · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.589037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdd913a4-78e6-47b2-8725-f71945240b74 · outbound

This paper cites MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.594169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48b5dd06-50fb-49ee-85c5-4336ba29726a · outbound

This paper cites LoRA-GA: Low-Rank Adaptation with Gradient Approximation.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LoRA-GA: Low-Rank Adaptation with Gradient Approximation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.598604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd5c68a9-e21b-4ee4-90ec-940560724613 · outbound

This paper cites LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.604093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b09f163-463c-4413-a6a1-5a82718f0ccd · outbound

This paper cites TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models TT-Rec: Tensor Train Compression for Deep Learning Recommendation Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.609357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c397a0d8-8d6c-4fd6-88e3-833261868875 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T23:12:34.613874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd6eb969-04b3-4f57-931e-bd543fece85b · outbound

This paper cites an unresolved cited work.

DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-10T23:12:35.022345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation c3632423-334d-47db-a5b7-d43468666cfa · inbound

Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging cites this paper.

Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:18:18.171673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.