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Paper Citation Record · LEDGER

HRP: High-Rank Preheating for Superior LoRA Initialization

As of 9 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2502.07739.

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

pith.paper-citation-record.v1
2502.07739 v3

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:51:10.457246Z

measured 62 of 62 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

62 of 62 outbound references displayed

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  • verified fuzzy13
  • unresolved43
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation d78085e1-0f15-4c17-a251-65b1de83c4ea · outbound

This paper cites GPT-4 Technical Report.

HRP: High-Rank Preheating for Superior LoRA Initialization GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-08T11:51:09.935617Z digest=sha256:3fc8457aac18b6fcd19d63d4c2b53a72849e5f42f0a12b3e1dede27b42bcfcc6

Observation 003ee60f-5673-4d56-a477-a643e2fd7e61 · outbound

This paper cites LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters.

HRP: High-Rank Preheating for Superior LoRA Initialization LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Reference 2

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Observation 9ca2d721-629a-4124-bc2b-51d635eccc00 · outbound

This paper cites LoRA Learns Less and Forgets Less.

HRP: High-Rank Preheating for Superior LoRA Initialization LoRA Learns Less and Forgets Less

Reference 3

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Observation 2eef8ede-ca9c-493b-a11b-54fb3d867758 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization On the Opportunities and Risks of Foundation Models

Reference 4

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source=pdf_text observed=2026-08-08T11:51:09.953937Z digest=sha256:6cbdab4424dc05eaff330602af7377b86ca4141401671f912cc571565256f898

Observation 7ed829f0-8d4c-475d-8d88-f8bd760f3237 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization OLoRA: Orthonormal Low-Rank Adaptation of Large Language Models

Reference 5

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Observation e3a2e738-3acc-45df-9555-dcd3f241ef68 · outbound

This paper cites Nonconvex optimization meets low-rank matrix factorization: An overview.

HRP: High-Rank Preheating for Superior LoRA Initialization Nonconvex optimization meets low-rank matrix factorization: An overview

Reference 6

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Observation 4f377922-c9ea-4771-b9cf-7c787e9f960d · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

HRP: High-Rank Preheating for Superior LoRA Initialization Training Verifiers to Solve Math Word Problems

Reference 7

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Observation 04a07925-a921-4de9-acd4-727ca4ebc31a · outbound

This paper cites Metainit: Initializing learning by learning to initialize.

HRP: High-Rank Preheating for Superior LoRA Initialization Metainit: Initializing learning by learning to initialize

Reference 8

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source=pdf_text observed=2026-08-08T11:51:09.981609Z digest=sha256:c213cbfb1ada5d67aa1f188826e292df2e69d02168b6f6b2cc80b345eb539c7e

Observation 1b9af9ac-46c9-4b81-812f-0fd32e2c7673 · outbound

This paper cites The approximation of one matrix by another of lower rank.

HRP: High-Rank Preheating for Superior LoRA Initialization The approximation of one matrix by another of lower rank

Reference 9

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Observation 55270172-619f-4622-b037-69b06f973298 · outbound

This paper cites Low rank adaptation for stable domain adaptation of vision transformers.

HRP: High-Rank Preheating for Superior LoRA Initialization Low rank adaptation for stable domain adaptation of vision transformers

Reference 10

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source=pdf_text observed=2026-08-08T11:51:09.995920Z digest=sha256:bcb451ff8943a5639f3db5c18eac5a4549b8e68ae90a67dda82aa500cee80101

Observation 363998b1-fdef-4514-9024-7338286c035d · outbound

This paper cites A Theoretical Survey on Foundation Models.

HRP: High-Rank Preheating for Superior LoRA Initialization A Theoretical Survey on Foundation Models

Reference 11

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source=pdf_text observed=2026-08-08T11:51:10.007479Z digest=sha256:1a26b038a7834c3153307849ecebbad02860d6fe2b81aa17c31242d89f43ea93

Observation 1f9eb1e0-4068-4d7e-8482-aca49966c0d8 · outbound

This paper cites Towards Theoretical Understandings of Self-Consuming Generative Models.

HRP: High-Rank Preheating for Superior LoRA Initialization Towards Theoretical Understandings of Self-Consuming Generative Models

Reference 12

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source=pdf_text observed=2026-08-08T11:51:10.017476Z digest=sha256:f8493396d65006e596caeb28aa198f63c6dc2b9b53c41911d919c48a97dc74b5

Observation 06292aff-f686-4025-9956-db01956e5d61 · outbound

This paper cites Understanding the difficulty of training deep feedfor- ward neural networks.

HRP: High-Rank Preheating for Superior LoRA Initialization Understanding the difficulty of training deep feedfor- ward neural networks

Reference 13

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Observation 50844b88-a383-412c-8985-949153816344 · outbound

This paper cites The Llama 3 Herd of Models.

HRP: High-Rank Preheating for Superior LoRA Initialization The Llama 3 Herd of Models

Reference 14

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Observation 8df582e0-ed47-4ba1-9433-599bbb0e72c0 · outbound

This paper cites The Impact of Initialization on LoRA Finetuning Dynamics.

HRP: High-Rank Preheating for Superior LoRA Initialization The Impact of Initialization on LoRA Finetuning Dynamics

Reference 15

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Observation 134b7460-80df-43db-9627-e5bb8e90c354 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization LoRA+: Efficient Low Rank Adaptation of Large Models

Reference 16

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Observation 851492bc-9bc1-415e-ac5d-8847100c14a0 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

HRP: High-Rank Preheating for Superior LoRA Initialization Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 17

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Observation c2c1008d-715d-4844-a503-398cc5e761c5 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

HRP: High-Rank Preheating for Superior LoRA Initialization Measuring Mathematical Problem Solving With the MATH Dataset

Reference 18

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Observation d2c02794-18ff-43d1-8609-03e38786fd08 · outbound

This paper cites The gronwall inequality.

HRP: High-Rank Preheating for Superior LoRA Initialization The gronwall inequality

Reference 19

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source=pdf_text observed=2026-08-08T11:51:10.080289Z digest=sha256:447b57b3a7608466a54c508cbdae317bd3f977355bf387301816a317391c65a4

Observation 391a5a18-0db7-4416-9f98-f9391fb8e0c5 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

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source=pdf_text observed=2026-08-08T11:51:10.089374Z digest=sha256:18743c63ba9a5aaa3281d194ce70fa60f67005b151f3bd9e92b8146466a8af09

Observation a41f7d7b-7040-44d1-9484-7601dfe22f2f · outbound

This paper cites Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation.

HRP: High-Rank Preheating for Superior LoRA Initialization Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation

Reference 21

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Observation fc812965-49fe-42ae-88c5-fb51f43a0586 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA

Reference 22

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Observation 5e036f4b-1cc4-42b9-a915-efbefba94605 · outbound

This paper cites VeRA: Vector-based Random Matrix Adaptation.

HRP: High-Rank Preheating for Superior LoRA Initialization VeRA: Vector-based Random Matrix Adaptation

Reference 23

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Observation 07bebc56-6a0d-4ce1-a516-e22093423f1c · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

HRP: High-Rank Preheating for Superior LoRA Initialization Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 24

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Observation 9e07cd81-3687-4bd8-8c4b-746f0309813f · outbound

This paper cites On the Crucial Role of Initialization for Matrix Factorization.

HRP: High-Rank Preheating for Superior LoRA Initialization On the Crucial Role of Initialization for Matrix Factorization

Reference 25

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Observation 3e5d7fcc-a844-421e-bda2-36a11b4a59ce · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.

HRP: High-Rank Preheating for Superior LoRA Initialization Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning

Reference 26

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Observation 2d9558d8-70f7-4622-88cb-96ab2b9e6fbe · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 27

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Observation c8bf0e7c-cf1b-46ba-a3b8-fb4cb8f702ab · outbound

This paper cites Decoupled weight decay regularization, 2019.

HRP: High-Rank Preheating for Superior LoRA Initialization Decoupled weight decay regularization, 2019

Reference 28

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source=pdf_text observed=2026-08-08T11:51:10.169443Z digest=sha256:647015806bb38d7ae3a747f6e3e67876a9585f2075d24dbab2712ce9ea479c74

Observation 89aabb06-e1ac-4319-82fa-7989181a9b0c · outbound

This paper cites Randomized Asymmetric Chain of LoRA: The First Meaningful Theoretical Framework for Low-Rank Adaptation.

HRP: High-Rank Preheating for Superior LoRA Initialization Randomized Asymmetric Chain of LoRA: The First Meaningful Theoretical Framework for Low-Rank Adaptation

Reference 29

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source=pdf_text observed=2026-08-08T11:51:10.182586Z digest=sha256:8f55b13b13f7f6fd85c6be7094ae8eec3d079393caae5a11f786449cfdc60c93

Observation 9a49474e-1d39-4312-be70-7f9993f53e3c · outbound

This paper cites A survey on lora of large language models.

HRP: High-Rank Preheating for Superior LoRA Initialization A survey on lora of large language models

Reference 30

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source=pdf_text observed=2026-08-08T11:51:10.191445Z digest=sha256:875c77ea69ed0a8cd450fa956c202990052d063f767b6ce1dd32c30034080686

Observation 21fb92ca-c8e9-4d03-b369-e30ca3d555af · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Reference 31

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source=pdf_text observed=2026-08-08T11:51:10.201271Z digest=sha256:a55798687fcf395753dc63c8369183e2527f2ff839597679414b1e961c23b2bd

Observation 06b7100f-60e7-4fc7-bd24-eb7bc1d4548f · outbound

This paper cites On the explicit role of initialization on the convergence and implicit bias of overparametrized linear networks.

HRP: High-Rank Preheating for Superior LoRA Initialization On the explicit role of initialization on the convergence and implicit bias of overparametrized linear networks

Reference 32

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source=pdf_text observed=2026-08-08T11:51:10.210611Z digest=sha256:0c276cb75fafa68167c2d95e3857467fdf3847dd43d705cd990242f635f0ba6c

Observation f88975d3-78c1-46a6-8658-9253fa0d5b5a · outbound

This paper cites All you need is a good init.

HRP: High-Rank Preheating for Superior LoRA Initialization All you need is a good init

Reference 33

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Observation c2d13bcb-0cae-4416-8e14-eaf8f0a48f83 · outbound

This paper cites Global convergence and stability of stochastic gradient descent.

HRP: High-Rank Preheating for Superior LoRA Initialization Global convergence and stability of stochastic gradient descent

Reference 34

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source=pdf_text observed=2026-08-08T11:51:10.228381Z digest=sha256:45a5f6ae2bcb52f87fdddb134bc64db432e714269fa30a9300519ea979bce5e0

Observation 53eb7a48-0809-41aa-9a9d-3f48faabb5b5 · outbound

This paper cites Initialization using update approximation is a silver bullet for extremely efficient low-rank fine-tuning.

HRP: High-Rank Preheating for Superior LoRA Initialization Initialization using update approximation is a silver bullet for extremely efficient low-rank fine-tuning

Reference 35

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Observation 73072fbe-8237-491c-8429-5c6a14701dcd · outbound

This paper cites an unresolved cited work.

HRP: High-Rank Preheating for Superior LoRA Initialization Unresolved cited work

Reference 36

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Observation 1cd322c7-f24f-4f1e-82c3-9220f1f8caaf · outbound

This paper cites Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying.

HRP: High-Rank Preheating for Superior LoRA Initialization Tied-Lora: Enhancing parameter efficiency of LoRA with weight tying

Reference 37

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Observation e6857a70-32f6-4768-9ff3-482cbf80d310 · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

HRP: High-Rank Preheating for Superior LoRA Initialization Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 38

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no resolver link, observed 2026-08-08T11:51:10.272377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.272377Z digest=sha256:a69e0e6f5580be98800569b41c172f85a45147af38f2dd720901f6e2ff72af62

Observation e0bfd0a2-3432-46db-bbdb-d24c886570ae · outbound

This paper cites ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank Adaptation.

HRP: High-Rank Preheating for Superior LoRA Initialization ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank Adaptation

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-08T11:51:10.783356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.285417Z digest=sha256:29dc7ac17bb941e1431c6094aece6c957d78d9f17f89fe0820093cad9229fb3a

Observation 47cfa5de-1d89-48ba-8830-5eb1b12a2bc6 · outbound

This paper cites Understanding the dynamics of gradient flow in overparameterized linear models.

HRP: High-Rank Preheating for Superior LoRA Initialization Understanding the dynamics of gradient flow in overparameterized linear models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.738000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.292761Z digest=sha256:59ccfcb0783108ba8040f1b5647ecfd42301f0cf5245e708d6ca197c086e47fd

Observation aece3599-8be2-48a2-8c8c-d90ce4ea84ac · outbound

This paper cites Gemma, 2024.

HRP: High-Rank Preheating for Superior LoRA Initialization Gemma, 2024

Reference 41

Resolution
parse uncertain
no resolver link, observed 2026-08-08T11:51:10.298966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.298966Z digest=sha256:bf53d0cb0af84089f560fb72a317bbae4ac63af3ce9d2522a9707a5dcf9f807e

Observation 46e47c93-22b0-4933-8e0e-03718129a6d2 · outbound

This paper cites Qwen3, April 2025.

HRP: High-Rank Preheating for Superior LoRA Initialization Qwen3, April 2025

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.706555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.306585Z digest=sha256:011edbafe25a287dbe7bcbb10e63a88c13254672920d219f182bbe6e6041072e

Observation 605b1842-b3cd-438b-b301-2aeb51d8ab32 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.314277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.314277Z digest=sha256:050c9564653ece16a5d9bba5434e2fffaa360f5f851c71a2a2b0e191fd20889a

Observation 910fe790-be67-4c51-a11d-2a325a3eaa25 · outbound

This paper cites RSVDPACK: An implementation of randomized algorithms for computing the singular value, interpolative, and CUR decompositions of matrices on multi-core and GPU architectures.

HRP: High-Rank Preheating for Superior LoRA Initialization RSVDPACK: An implementation of randomized algorithms for computing the singular value, interpolative, and CUR decompositions of matrices on multi-core and GPU architectures

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-08T11:51:10.737815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.327030Z digest=sha256:e4a11816692a73d231805a90a5185b44ff7e73cfbbbd5f3b9d4e37047b13d501

Observation 69f927ee-778f-4ee1-8fb2-f988c66b1cb6 · outbound

This paper cites GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding.

HRP: High-Rank Preheating for Superior LoRA Initialization GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.336035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.336035Z digest=sha256:78a5d1a365d88a81e9f65ab96729ae71cf88ec7ca9d8fddb8a47f58a215ee8ee

Observation 70d69d17-4c1b-4d6f-bd02-2a9155093fbb · outbound

This paper cites Pufferfish: Communication- efficient models at no extra cost.

HRP: High-Rank Preheating for Superior LoRA Initialization Pufferfish: Communication- efficient models at no extra cost

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.689185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.344163Z digest=sha256:e0c742a89b4885f6d3bc2c00d0c173fecbd0ab9beccbed3d609930a397873db4

Observation 92cd651b-c34c-4aeb-946f-19324625ff71 · outbound

This paper cites Cuttlefish: Low-rank model training without all the tuning.

HRP: High-Rank Preheating for Superior LoRA Initialization Cuttlefish: Low-rank model training without all the tuning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.670340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.350927Z digest=sha256:ea3fb34058712b60b1873d3ab2a2dd5864925b774ff89a1daf31ab5a76f20925

Observation 16c7bea6-2db8-42e7-8c08-7b110304cfd2 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization LoRA-GA: Low-Rank Adaptation with Gradient Approximation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.356322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.356322Z digest=sha256:487574fab5e3781a4feadfa72b993480ec2c86355d1a7f7e07e50ed7c12270cd

Observation 6ba59ee3-fbbb-4d8e-9613-eca5e0f47e52 · outbound

This paper cites Implicit Regularization Makes Overparameterized Asymmetric Matrix Sensing Robust to Perturbations.

HRP: High-Rank Preheating for Superior LoRA Initialization Implicit Regularization Makes Overparameterized Asymmetric Matrix Sensing Robust to Perturbations

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-08T11:51:10.670710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.361596Z digest=sha256:e0b09d3fe192d12390f836cb3579e1fa54225a65a4bdad45d1e0720c3c0b6664

Observation 4d2440e1-5467-40fe-a287-2a3902ad38b2 · outbound

This paper cites Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning.

HRP: High-Rank Preheating for Superior LoRA Initialization Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.367578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.367578Z digest=sha256:f17e384680241760f21e7ae687f4e8644663d3081236b3af88a7cf4476f21afc

Observation e22cd51e-d268-492c-94dd-c342b7f3b830 · outbound

This paper cites Towards theoretically inspired neural initialization optimization.

HRP: High-Rank Preheating for Superior LoRA Initialization Towards theoretically inspired neural initialization optimization

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.654365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.373841Z digest=sha256:15080e3a46a059e8d59175c91781633382614d191fcdceae59181acf31e08a4c

Observation 4b5debd4-1245-4c42-9332-da9fb09804c8 · outbound

This paper cites Global convergence of gradient descent for asymmetric low-rank matrix factorization.

HRP: High-Rank Preheating for Superior LoRA Initialization Global convergence of gradient descent for asymmetric low-rank matrix factorization

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.636740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.380158Z digest=sha256:ec0bb445b8e384742617a2dfbd30b3874ddd1762640af1fa5ff8c349503c356e

Observation 78c3e74a-8cac-4703-a39b-3ee0c80e60a6 · outbound

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

HRP: High-Rank Preheating for Superior LoRA Initialization MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.387445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.387445Z digest=sha256:62f6e1e4e48a66e473d62d4fc6ae023d9c0d5c00ff10f843e165ad3dc70dea97

Observation ecc18705-64e5-405e-b2f4-86c2f65579a2 · outbound

This paper cites The Expressive Power of Low-Rank Adaptation.

HRP: High-Rank Preheating for Superior LoRA Initialization The Expressive Power of Low-Rank Adaptation

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.397272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.397272Z digest=sha256:ae9f7e3f643e34bd7197fb4b4b7daa29510dfb125cd38b1962bc82dfcdca5c8b

Observation 5757111b-d92f-4edb-bf8e-3df4cc52fd73 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

HRP: High-Rank Preheating for Superior LoRA Initialization AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.406460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.406460Z digest=sha256:0c23dc035b2cec03a40cd84594c42a70ae37698f46cf118e40cfaf7f494b7f79

Observation 41f64ce0-11a0-45e9-8d5a-32f7248d4bc7 · outbound

This paper cites Gradinit: Learning to initialize neural networks for stable and efficient training.

HRP: High-Rank Preheating for Superior LoRA Initialization Gradinit: Learning to initialize neural networks for stable and efficient training

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.413134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.413134Z digest=sha256:ce868bafc983d68f379c80ac653b148b8cd97ce7ba5796a402007796bcacf124

Observation b2e6ad81-fa2c-45ab-a33c-de9b21d48279 · outbound

This paper cites Asymmetry in Low-Rank Adapters of Foundation Models.

HRP: High-Rank Preheating for Superior LoRA Initialization Asymmetry in Low-Rank Adapters of Foundation Models

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T11:51:10.421410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:51:10.421410Z digest=sha256:0dd8ca9127c48e31080fcb3116eb5561d26cc7c326040cca079ca8dee0427ae0

Observation 1e53aac3-b5e1-4557-b4bc-ae6ee6a44433 · outbound

This paper cites an unresolved cited work.

HRP: High-Rank Preheating for Superior LoRA Initialization Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:51:11.603534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.429022Z digest=sha256:44e46d792e077d17a837ec320a9b7f6087b34877d038bde3dc1363cb35f8defc

Observation 131178c3-9cca-4d28-836a-90e9ce0af0e3 · outbound

This paper cites an unresolved cited work.

HRP: High-Rank Preheating for Superior LoRA Initialization Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:51:11.584401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.435196Z digest=sha256:ef8f41a4879f9e2fdb3a996b0952f21a3607b026c088ba1bc3b2d71fa804190c

Observation 262c365c-d727-4536-b9ea-61b17775ad5c · outbound

This paper cites an unresolved cited work.

HRP: High-Rank Preheating for Superior LoRA Initialization Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:51:11.565162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.441859Z digest=sha256:4837992e1ae415d18678575db680fda81bc9c6a805a85d1c0ac62c836d04fec7

Observation 55955c17-825e-4802-9410-c4b1071fafd8 · outbound

This paper cites an unresolved cited work.

HRP: High-Rank Preheating for Superior LoRA Initialization Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:51:11.546646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.449915Z digest=sha256:1fe96ff6c21bebc3d288db0b72ccf29a7d7ec6c5bb709fc4775adc210b247a6b

Observation f485d9bc-e6d3-4c50-b59a-beb6fc29c47c · outbound

This paper cites tilde” variables as those from Asymmetric LoRA, while the without “tilde.

HRP: High-Rank Preheating for Superior LoRA Initialization tilde” variables as those from Asymmetric LoRA, while the without “tilde

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T11:51:11.529347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T11:51:10.457246Z digest=sha256:a6c18ccfab5c77bbbfb89990240abd881931a0345ab80e02f1729a8586a638e9

Pith citing papers

No inbound Pith citation observations are available.