Paper Citation Record · LEDGER

Implementing Adaptations for Vision AutoRegressive Model

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2507.11441.

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

pith.paper-citation-record.v1
2507.11441 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:12:35.096296Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

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.

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

36 of 36 outbound references displayed

verified exact0
verified fuzzy5
unresolved31
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External citation measurements

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Outbound references

Observation 0c90350c-2a22-4542-9c81-859062c4dd61 · outbound

This paper cites write newline.

Implementing Adaptations for Vision AutoRegressive Model write newline

Reference 1

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Observation c890b693-9045-48aa-96fa-d727bf08752f · outbound

This paper cites http://yann.

Implementing Adaptations for Vision AutoRegressive Model http://yann

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:12:36.242691Z

Source-reported events for the cited work

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Observation 9cc786a1-d275-4cb1-aa86-949d6067b3ff · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Implementing Adaptations for Vision AutoRegressive Model Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 3

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Observation 600160cd-d5ce-41ba-928c-9f98e16bd8cd · outbound

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

Implementing Adaptations for Vision AutoRegressive Model Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning

Reference 4

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Observation 5d9b6360-de3e-40c9-8f1b-eac5f1368c21 · outbound

This paper cites Food-101--mining discriminative components with random forests.

Implementing Adaptations for Vision AutoRegressive Model Food-101--mining discriminative components with random forests

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:12:36.117327Z

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Observation 3a5adf39-b965-4fd0-a1af-75111316ce11 · outbound

This paper cites Generative pretraining from pixels.

Implementing Adaptations for Vision AutoRegressive Model Generative pretraining from pixels

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:12:35.968549Z

Source-reported events for the cited work

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Observation dc0524fd-a423-48a6-b5a9-f1ca69f309b5 · outbound

This paper cites Unlocking High-Accuracy Differentially Private Image Classification through Scale.

Implementing Adaptations for Vision AutoRegressive Model Unlocking High-Accuracy Differentially Private Image Classification through Scale

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:32.873379Z

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Observation 37c2dd28-f928-4858-8153-af136a65892a · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Implementing Adaptations for Vision AutoRegressive Model Imagenet: A large-scale hierarchical image database

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:32.952771Z

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Observation 2d8060dd-9d17-47d2-957a-de1e3f6aac04 · outbound

This paper cites Differentially Private Diffusion Models.

Implementing Adaptations for Vision AutoRegressive Model Differentially Private Diffusion Models

Reference 9

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Observation c9f6913a-bccb-4eb0-886d-797d246a7230 · outbound

This paper cites Differential privacy.

Implementing Adaptations for Vision AutoRegressive Model Differential privacy

Reference 10

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Observation 28b79783-b42a-469c-b48c-7fbd7ad82f31 · outbound

This paper cites Taming transformers for high-resolution image synthesis, 2020.

Implementing Adaptations for Vision AutoRegressive Model Taming transformers for high-resolution image synthesis, 2020

Reference 11

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Observation 1e768c62-a056-4f98-9255-a6496f53dfa8 · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion.

Implementing Adaptations for Vision AutoRegressive Model An image is worth one word: Personalizing text-to-image generation using textual inversion

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:12:35.796168Z

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.

Observation 8475ac6b-768b-4585-8965-4a3c27e1a75f · outbound

This paper cites Differentially Private Diffusion Models Generate Useful Synthetic Images.

Implementing Adaptations for Vision AutoRegressive Model Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 13

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Observation d479108d-e84d-402d-88d1-93f57421a113 · outbound

This paper cites Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis.

Implementing Adaptations for Vision AutoRegressive Model Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis

Reference 14

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Observation 0fb0cb18-152b-4064-b1cd-c4dccadd7b05 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Implementing Adaptations for Vision AutoRegressive Model Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 15

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Observation 99669903-7792-4d78-9315-779ec8b05361 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Implementing Adaptations for Vision AutoRegressive Model Lora: Low-rank adaptation of large language models

Reference 16

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Observation f695b650-ff0b-4dce-9126-3296de6e4daf · outbound

This paper cites Diffusion models in medical imaging: A comprehensive survey.

Implementing Adaptations for Vision AutoRegressive Model Diffusion models in medical imaging: A comprehensive survey

Reference 17

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Observation bbd394b9-45b3-4c0d-a2fb-f75a07e244cf · outbound

This paper cites 3d object representations for fine-grained categorization.

Implementing Adaptations for Vision AutoRegressive Model 3d object representations for fine-grained categorization

Reference 18

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Observation 611f8366-abe7-47a5-b68f-2005e7d4eb0b · outbound

This paper cites Improved precision and recall metric for assessing generative models.

Implementing Adaptations for Vision AutoRegressive Model Improved precision and recall metric for assessing generative models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:12:35.643439Z

Source-reported events for the cited work

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Observation b7511a60-a1d4-4199-9544-10389ab7519e · outbound

This paper cites DP-LDMs: Differentially Private Latent Diffusion Models.

Implementing Adaptations for Vision AutoRegressive Model DP-LDMs: Differentially Private Latent Diffusion Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:33.883885Z

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Observation c7871ce9-d40f-48e7-aa8c-0d97ec0a1820 · outbound

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

Implementing Adaptations for Vision AutoRegressive Model Automated flower classification over a large number of classes

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:33.963363Z

Source-reported events for the cited work

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Observation 6034052a-f96a-4bf1-8b7d-edf7ee08dd3d · outbound

This paper cites Cats and dogs.

Implementing Adaptations for Vision AutoRegressive Model Cats and dogs

Reference 22

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Observation 8be747e0-af40-4475-9e15-cbc9267597e9 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Implementing Adaptations for Vision AutoRegressive Model PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 23

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Observation bdbbec8f-9eb8-437b-8eba-aba662f0bbcb · outbound

This paper cites Scalable diffusion models with transformers.

Implementing Adaptations for Vision AutoRegressive Model Scalable diffusion models with transformers

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.231940Z

Source-reported events for the cited work

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Observation 2562607e-a57a-4cd2-aa1c-b4a600afd7ab · outbound

This paper cites Language models are unsupervised multitask learners.

Implementing Adaptations for Vision AutoRegressive Model Language models are unsupervised multitask learners

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.308692Z

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Observation cae3739f-80e9-4eee-81a4-2a80de79b329 · outbound

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

Implementing Adaptations for Vision AutoRegressive Model High-resolution image synthesis with latent diffusion models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.378014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c5fd95f-b442-4e0c-89b5-01d0dec64f8b · outbound

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

Implementing Adaptations for Vision AutoRegressive Model Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.431501Z

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Observation 768600e0-ad0e-4fab-8e67-035dfd8c78f6 · outbound

This paper cites Assessing Generative Models via Precision and Recall.

Implementing Adaptations for Vision AutoRegressive Model Assessing Generative Models via Precision and Recall

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.524953Z

Source-reported events for the cited work

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Observation b085723f-8da0-459c-b4b6-83be057144a1 · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

Implementing Adaptations for Vision AutoRegressive Model Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.614860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc92a7ff-fd65-43d3-91e9-1977cd9dddbd · outbound

This paper cites Differentially Private Fine-Tuning of Diffusion Models.

Implementing Adaptations for Vision AutoRegressive Model Differentially Private Fine-Tuning of Diffusion Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.690919Z

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Observation 1a064ef9-acb4-4892-a93b-fdd153210ead · outbound

This paper cites Attention is all you need.

Implementing Adaptations for Vision AutoRegressive Model Attention is all you need

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.764595Z

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Observation 7fa1a9f5-3902-49c0-8319-a6d16f987e13 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Implementing Adaptations for Vision AutoRegressive Model The caltech-ucsd birds-200-2011 dataset

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.834877Z

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Observation e33de21c-4eaf-42ca-a112-b1c839a7aab9 · outbound

This paper cites DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning.

Implementing Adaptations for Vision AutoRegressive Model DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.897147Z

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Unavailable: canonical work link unavailable.

Observation 0f2ced8f-88ea-4c83-9a8a-2b6a08e53a1b · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Implementing Adaptations for Vision AutoRegressive Model Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:34.961767Z

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Unavailable: canonical work link unavailable.

Observation 3a065fbe-2096-4956-bce2-2ed9304f5d3e · outbound

This paper cites Randomized Autoregressive Visual Generation.

Implementing Adaptations for Vision AutoRegressive Model Randomized Autoregressive Visual Generation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:35.021735Z

Source-reported events for the cited work

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Observation 0f0b55f4-82b3-490c-8f5a-67266f026894 · outbound

This paper cites Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning.

Implementing Adaptations for Vision AutoRegressive Model Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:12:35.096296Z

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Pith citing papers

No inbound Pith citation observations are available.