Paper Citation Record · LEDGER

Backbone Augmented Training for Adaptations

As of 22 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2506.04288.

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

pith.paper-citation-record.v1
2506.04288 v1

Coverage vector

measured 51 of 51 reference resolution

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measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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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.

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation 40324eaf-c2c2-41ba-9ab6-12e40780552a · outbound

This paper cites an unresolved cited work.

Backbone Augmented Training for Adaptations Unresolved cited work

Reference 1

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Observation a6e6ef1e-62d9-4fd0-8427-67c488c99a48 · outbound

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

Backbone Augmented Training for Adaptations High- resolution image synthesis with latent diffusion models

Reference 2

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Observation 34df0948-2772-47ae-9519-9d41cddc3d44 · outbound

This paper cites The llama 3 herd of models, 2024.

Backbone Augmented Training for Adaptations The llama 3 herd of models, 2024

Reference 3

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Observation ce37613c-5d40-45ae-ada7-dcbb3bab2468 · outbound

This paper cites Scalable diffusion models with transformers, 2023.

Backbone Augmented Training for Adaptations Scalable diffusion models with transformers, 2023

Reference 4

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Observation c9745ed4-52c9-4e99-bc2f-683e26b90f62 · outbound

This paper cites Fast high-resolution image synthesis with latent adversarial diffusion distillation, 2024.

Backbone Augmented Training for Adaptations Fast high-resolution image synthesis with latent adversarial diffusion distillation, 2024

Reference 5

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Observation 78ab835c-24c5-44e7-9bf1-bd9c85d7e70a · outbound

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

Backbone Augmented Training for Adaptations LoRA: Low-Rank Adaptation of Large Language Models

Reference 6

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Observation fd86769b-cdaa-43b7-b096-d6efd51f2f86 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms, 2023.

Backbone Augmented Training for Adaptations Qlora: Efficient finetuning of quantized llms, 2023

Reference 7

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Observation 781c31e8-4d6c-460f-be63-d4a9b0ee319d · outbound

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

Backbone Augmented Training for Adaptations DoRA: Weight-Decomposed Low-Rank Adaptation

Reference 8

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Observation c9ff7912-25c2-4262-8fba-32bf3945bdb5 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation, 2023.

Backbone Augmented Training for Adaptations Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation, 2023

Reference 9

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Observation 8d2d40aa-df9c-471d-bf7d-0e926a5d950d · outbound

This paper cites Bermano, Gal Chechik, and Daniel Cohen-Or.

Backbone Augmented Training for Adaptations Bermano, Gal Chechik, and Daniel Cohen-Or

Reference 10

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Observation d62428e3-af4a-4ec2-b345-5920a06b4572 · outbound

This paper cites Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models, 2023.

Backbone Augmented Training for Adaptations Hyperdreambooth: Hypernetworks for fast personalization of text-to-image models, 2023

Reference 11

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Observation 37c11b2f-3fc5-4f69-b6d2-3044dda01215 · outbound

This paper cites Enhancing dreambooth with lora for generating unlimited characters with stable diffusion, 06 2024.

Backbone Augmented Training for Adaptations Enhancing dreambooth with lora for generating unlimited characters with stable diffusion, 06 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:00:39.396239Z

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Observation 3494773c-6ff7-4ae5-ace9-8570f2afdba8 · outbound

This paper cites Overfitting mechanism and avoidance in deep neural networks, 2019.

Backbone Augmented Training for Adaptations Overfitting mechanism and avoidance in deep neural networks, 2019

Reference 13

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Observation e6382f9e-0e3b-4015-a0d3-bceeadcca439 · outbound

This paper cites White, and Sujay Kumar Jauhar.

Backbone Augmented Training for Adaptations White, and Sujay Kumar Jauhar

Reference 14

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Observation 6c756180-e64d-4b86-a38f-668e8c2b60fc · outbound

This paper cites Nlp evaluation in trouble: On the need to measure llm data contamination for each benchmark, 2023.

Backbone Augmented Training for Adaptations Nlp evaluation in trouble: On the need to measure llm data contamination for each benchmark, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:00:39.297394Z

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Observation a67a2a0a-d6dd-456f-a964-de3a11b6d73e · outbound

This paper cites Does synthetic data make large language models more efficient?, 2023.

Backbone Augmented Training for Adaptations Does synthetic data make large language models more efficient?, 2023

Reference 16

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Observation 4d1f0ebf-508c-4636-9f0b-64cf864e402d · outbound

This paper cites Aligning Instruction Tuning with Pre-training.

Backbone Augmented Training for Adaptations Aligning Instruction Tuning with Pre-training

Reference 17

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Observation 91fdfbfd-f53b-4cc8-a453-547a7d000825 · outbound

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Backbone Augmented Training for Adaptations Unresolved cited work

Reference 18

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Observation 2b233980-64ff-4cab-baea-7867ec38bf2a · outbound

This paper cites Improved fine-tuning by better leveraging pre-training data, 2022.

Backbone Augmented Training for Adaptations Improved fine-tuning by better leveraging pre-training data, 2022

Reference 19

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Observation edf1eec3-dda0-4aed-92ca-3570a8a20aa2 · outbound

This paper cites Sdxl photorealistic lora tips: Reflections on training and releasing 10 different models, 2024.

Backbone Augmented Training for Adaptations Sdxl photorealistic lora tips: Reflections on training and releasing 10 different models, 2024

Reference 20

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Backbone Augmented Training for Adaptations Unresolved cited work

Reference 21

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Observation 0a0128ea-f7e0-4475-8361-4088ecbd100e · outbound

This paper cites Towards a statistical theory of data selection under weak supervision.

Backbone Augmented Training for Adaptations Towards a statistical theory of data selection under weak supervision

Reference 22

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Observation 8430fa28-29c3-4e79-8821-eb4833b54040 · outbound

This paper cites Datainf: Efficiently estimating data influence in lora-tuned llms and diffusion models, 2024.

Backbone Augmented Training for Adaptations Datainf: Efficiently estimating data influence in lora-tuned llms and diffusion models, 2024

Reference 23

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This paper cites Parameter-efficient transfer learning for nlp.

Backbone Augmented Training for Adaptations Parameter-efficient transfer learning for nlp

Reference 24

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This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Backbone Augmented Training for Adaptations Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 25

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This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.

Backbone Augmented Training for Adaptations Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models

Reference 26

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Backbone Augmented Training for Adaptations Parameter-Efficient Transfer Learning with Diff Pruning

Reference 27

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This paper cites Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning.

Backbone Augmented Training for Adaptations Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 28

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Backbone Augmented Training for Adaptations Compacter: Efficient low-rank hypercomplex adapter layers

Reference 29

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Backbone Augmented Training for Adaptations Denoising diffusion implicit models, 2022

Reference 30

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Backbone Augmented Training for Adaptations Denoising diffusion probabilistic models

Reference 31

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This paper cites Navigating text-to-image customization: From lycoris fine-tuning to model evaluation.

Backbone Augmented Training for Adaptations Navigating text-to-image customization: From lycoris fine-tuning to model evaluation

Reference 32

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Backbone Augmented Training for Adaptations Unresolved cited work

Reference 33

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Backbone Augmented Training for Adaptations Infobatch: Lossless training speed up by unbiased dynamic data pruning

Reference 34

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This paper cites Wang, Tianji Yang, James Zou, Yongchan Kwon, and Ruoxi Jia.

Backbone Augmented Training for Adaptations Wang, Tianji Yang, James Zou, Yongchan Kwon, and Ruoxi Jia

Reference 35

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Observation aa5d424e-6939-44c0-9412-4c9e87721658 · outbound

This paper cites Optimal sub-sampling with influence functions, 2017.

Backbone Augmented Training for Adaptations Optimal sub-sampling with influence functions, 2017

Reference 36

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Observation cfa7bba5-c4c0-4eec-91de-eb6d9c186f5e · outbound

This paper cites Less is better: Unweighted data subsampling via influence function, 2021.

Backbone Augmented Training for Adaptations Less is better: Unweighted data subsampling via influence function, 2021

Reference 37

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This paper cites A statistical perspective on algorithmic leveraging.

Backbone Augmented Training for Adaptations A statistical perspective on algorithmic leveraging

Reference 38

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Backbone Augmented Training for Adaptations New insights and perspectives on the natural gradient method

Reference 39

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Backbone Augmented Training for Adaptations Unresolved cited work

Reference 40

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Observation a294163b-4213-42ad-a0d6-7ffb67d7ffe6 · outbound

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Backbone Augmented Training for Adaptations Optimal subsampling algorithms for big data regressions

Reference 41

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Backbone Augmented Training for Adaptations Laion-5b: An open large-scale dataset for training next generation image-text models, 2022

Reference 42

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Backbone Augmented Training for Adaptations The star wars dataverse, 2024

Reference 43

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Observation 9716aea4-2da3-40c5-8439-2d45ad2225e5 · outbound

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

Backbone Augmented Training for Adaptations Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 44

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Observation 1f2b07d0-5be7-4481-9c1d-4c86de187799 · outbound

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Backbone Augmented Training for Adaptations HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 46

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Backbone Augmented Training for Adaptations An introduction to measure theory, volume 126

Reference 47

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Backbone Augmented Training for Adaptations Hashimoto

Reference 48

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Observation 312feaf1-f51c-45e9-82cf-c9b813660e6a · outbound

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Backbone Augmented Training for Adaptations A question-entailment approach to question answering

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:00:38.513853Z

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Observation 4d32b1a5-d1d2-488d-b522-7b01020dabc5 · outbound

This paper cites Winogrande: An adversarial winograd schema challenge at scale.

Backbone Augmented Training for Adaptations Winogrande: An adversarial winograd schema challenge at scale

Reference 50

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This paper cites Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization.

Backbone Augmented Training for Adaptations Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Reference 51

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Observation d1f179e5-0a15-4ec0-af71-727be8ed1dc1 · outbound

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Backbone Augmented Training for Adaptations Star Wars

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:00:38.458099Z

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Pith citing papers

No inbound Pith citation observations are available.