Paper Citation Record · LEDGER

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

As of 5 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 1 inbound Pith citation observation for arXiv:2604.08749.

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

pith.paper-citation-record.v1
2604.08749 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:54:59.245970Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:06:33.360765Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T00:06:34.033696Z

Reference resolution

47 of 47 outbound references displayed

verified exact8
verified fuzzy30
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 96949bfe-4b6a-4be6-a6fc-58a992111216 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:54:37.978009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 49fcfe35-62bc-4fd5-b6d8-0a63f667ec48 · outbound

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

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need LoRA: Low-Rank Adaptation of Large Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-11T07:55:59.213707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bae97482-bec5-4f52-9273-2f83fe867b44 · outbound

This paper cites Intrinsic dimensionality ex- plains the effectiveness of language model fine-tuning.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Intrinsic dimensionality ex- plains the effectiveness of language model fine-tuning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:54:37.981509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7939cefc-07c4-4ffb-b0e3-164d9f55c72f · outbound

This paper cites echo state.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need echo state

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.689504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4b3df5ae-8709-46a0-b50a-39cdc4959ad4 · outbound

This paper cites Real-time computing without stable states: A new framework for neural computation based on perturba- tions.Neural Computation, 14(11):2531– 2560.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Real-time computing without stable states: A new framework for neural computation based on perturba- tions.Neural Computation, 14(11):2531– 2560

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.756642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2ce76b47-c626-4179-853d-2369b20159bb · outbound

This paper cites Manevitz.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Manevitz

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.685222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a07d2fc0-15a6-4ed8-8c26-fefd8c1cff3d · outbound

This paper cites Memory via Temporal Delays in weightless Spiking Neural Network.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Memory via Temporal Delays in weightless Spiking Neural Network

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:59.249013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6319f746-4e31-4e4e-820b-185038f1294f · outbound

This paper cites Reservoir transformers.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Reservoir transformers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.765046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ada6b6fa-08dd-40ef-a8a7-fd78c9ffde80 · outbound

This paper cites Attention is all you need.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Attention is all you need

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.732587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fd4a9c62-2b9d-4ab9-a16e-e67663085d54 · outbound

This paper cites Algorith- mic capabilities of random transformers.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Algorith- mic capabilities of random transformers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.743148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8a585f32-0c80-4211-8ce2-4c498a72cbbd · outbound

This paper cites 2025 , eprint =.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need 2025 , eprint =

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T07:55:59.252834Z

Source-reported events for the cited work

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Observation c9005dce-ea20-4682-9129-a62b21484aa4 · outbound

This paper cites Measuring the in- trinsic dimension of objective landscapes.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Measuring the in- trinsic dimension of objective landscapes

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.679852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6ce13321-1b6a-4cf9-a1df-f53d26ee5336 · outbound

This paper cites Hyperdimensional com- puting: An introduction to computing in distributed representation with high- dimensional random vectors.Cognitive Computation, 1(2):139–159.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Hyperdimensional com- puting: An introduction to computing in distributed representation with high- dimensional random vectors.Cognitive Computation, 1(2):139–159

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.702974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4ea81772-828e-4160-8951-6e4334b9b88e · outbound

This paper cites Rachkovskij, Evgeny Osipov, and Abbas Rahimi.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Rachkovskij, Evgeny Osipov, and Abbas Rahimi

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.710735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 247b72cf-fb77-44af-bd7c-ed05a2003994 · outbound

This paper cites Predicting in-hospital mortality of ICU patients: The PhysioNet/Computing in Cardiology Chal- lenge 2012.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Predicting in-hospital mortality of ICU patients: The PhysioNet/Computing in Cardiology Chal- lenge 2012

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.794802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0f55af9d-0a25-4c7d-ac48-42b5c3d4160e · outbound

This paper cites Liq- uid time-constant networks.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Liq- uid time-constant networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.749928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9aee7ef7-df57-4334-939a-24afecfa2f40 · outbound

This paper cites Closed- form continuous-time neural networks.Na- ture Machine Intelligence, 4:992–1003.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Closed- form continuous-time neural networks.Na- ture Machine Intelligence, 4:992–1003

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.739925Z

Source-reported events for the cited work

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Observation 95248f67-185c-4d92-8b21-3f592a48e8f9 · outbound

This paper cites Deep residual learning for image recognition.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Deep residual learning for image recognition

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.759519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6b55f86e-1914-4957-a3e4-decaf73cd4ea · outbound

This paper cites Decision transformer: Rein- forcement learning via sequence modeling.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Decision transformer: Rein- forcement learning via sequence modeling

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.780506Z

Source-reported events for the cited work

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Observation 05c744bc-e60a-4d1e-bc40-0b0252405957 · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Open graph benchmark: Datasets for machine learning on graphs

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.771166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f8c36585-4bf8-4a58-a7e7-d85604ce01e5 · outbound

This paper cites How powerful are graph neural networks? InInternational Confer- ence on Learning Representations.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need How powerful are graph neural networks? InInternational Confer- ence on Learning Representations

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.729140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4c32bd56-f3a3-4ed6-b58b-4c7a8d7a4990 · outbound

This paper cites Kipf and Max Welling.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Kipf and Max Welling

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.786068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fb6700f4-a95c-454e-a751-c7df7ae0a913 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need An image is worth 16x16 words: Transformers for image recognition at scale

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.791980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c9cc3b0-c609-4640-8b15-5ce54e2c92e9 · outbound

This paper cites Automated flower classification over a large number of classes.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Automated flower classification over a large number of classes

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.717783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ee6a416e-e285-490c-9dee-f787e3d83c52 · outbound

This paper cites Learning word vec- tors for sentiment analysis.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Learning word vec- tors for sentiment analysis

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.721860Z

Source-reported events for the cited work

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Observation 344d9916-2bdc-4da6-8a6f-4572f352d596 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-11T07:55:59.210310Z

Source-reported events for the cited work

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Observation 0c7ac6ae-64d2-4590-8f04-3652e4d1fb8a · outbound

This paper cites Pointer Sentinel Mixture Models.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Pointer Sentinel Mixture Models

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-11T07:55:59.233371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6bdeecac-6521-405e-9013-187aee4d7451 · outbound

This paper cites Training Compute-Optimal Large Language Models.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Training Compute-Optimal Large Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-11T07:55:59.262964Z

Source-reported events for the cited work

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Observation aa0c4843-f83e-465c-81f3-22a8588f6cd8 · outbound

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

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need LLaMA: Open and Efficient Foundation Language Models

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-11T07:55:59.240503Z

Source-reported events for the cited work

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Observation ff4b5f09-bc63-4ef8-9357-fcfb49052c73 · outbound

This paper cites XNOR- Net: ImageNet classification using binary convolutional neural networks.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need XNOR- Net: ImageNet classification using binary convolutional neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.725448Z

Source-reported events for the cited work

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Observation a9438554-ffc2-4d57-b76b-b48fafa31944 · outbound

This paper cites Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:55:59.244855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4b760dbd-65a7-47df-9699-4cf6240ab093 · outbound

This paper cites Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bha- tia, Nan Boden, Al Borchers, et al.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bha- tia, Nan Boden, Al Borchers, et al

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.774297Z

Source-reported events for the cited work

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Observation 33be45ed-8634-4e9a-93dc-02ac4824b849 · outbound

This paper cites There’s plenty of room right here: Biological sys- tems as evolved, overloaded, multi-scale ma- chines.Biomimetics, 8(1).

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need There’s plenty of room right here: Biological sys- tems as evolved, overloaded, multi-scale ma- chines.Biomimetics, 8(1)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.707135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 44cfcd9c-633f-4400-b202-dc18ce928794 · outbound

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

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:05:50.945454Z

Source-reported events for the cited work

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Observation e020cc7d-1634-4700-8c0c-fdb24b77a8e9 · outbound

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

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need DoRA: Weight-decomposed low- rank adaptation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.736189Z

Source-reported events for the cited work

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Observation 6f636a02-8693-454b-8795-b7f5b3797669 · outbound

This paper cites Compe- tency in navigating arbitrary spaces as an invariant for analyzing cognition in diverse embodiments.Entropy, 24(6).

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Compe- tency in navigating arbitrary spaces as an invariant for analyzing cognition in diverse embodiments.Entropy, 24(6)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.664686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c70da691-3cab-479d-a087-6a1b009f94bf · outbound

This paper cites A theoretical perspective on hyperdimensional computing.Journal of Artificial Intelligence Research, 72:215–249.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need A theoretical perspective on hyperdimensional computing.Journal of Artificial Intelligence Research, 72:215–249

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.777426Z

Source-reported events for the cited work

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Observation 6d8664b6-0a2b-4ac8-a067-a80628ba5011 · outbound

This paper cites Gallego, Matthew G.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Gallego, Matthew G

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.762411Z

Source-reported events for the cited work

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Observation d2156256-9c02-4e24-9f98-02934ecd55c2 · outbound

This paper cites Internal.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Internal

Reference 39

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Observation f6779369-1ac1-474f-9b61-9fab51d48b06 · outbound

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A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 40

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Observation 7bf941ff-50ae-41e0-9d1f-2ba989e9881d · outbound

This paper cites an unresolved cited work.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 41

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Observation d6726139-01bb-452f-950d-f86fad37647a · outbound

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A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 42

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Source-reported events for the cited work

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Observation 5510012a-be2b-4bc2-bcea-8582700c1006 · outbound

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A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 43

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Source-reported events for the cited work

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Observation 8aae167f-03d8-4664-a25f-fda1d379efdb · outbound

This paper cites an unresolved cited work.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:59:36.788962Z

Source-reported events for the cited work

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Observation 44bbff73-14ac-4a9b-9142-18371268dfa1 · outbound

This paper cites an unresolved cited work.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:59:36.768099Z

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Observation da64cb02-fab0-4eaa-bcf3-5dbcea39d9b1 · outbound

This paper cites an unresolved cited work.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need Unresolved cited work

Reference 46

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:59:36.783355Z

Source-reported events for the cited work

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Observation 67dd8e36-581f-474b-ad4b-432148c6d3be · outbound

This paper cites The LoRA adapter compensates for // the specific choice; only the seed must be recorded.

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need The LoRA adapter compensates for // the specific choice; only the seed must be recorded

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:59:36.698352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation 78c2cf46-b90f-4a6e-928d-1af38a96d8ad · inbound

Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models cites this paper.

Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

Reference 2026

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T00:06:34.080579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.