Paper Citation Record · LEDGER

Whitened CLIP as a Likelihood Surrogate of Images and Captions

As of 20 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2505.06934.

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

pith.paper-citation-record.v1
2505.06934 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:34:17.989815Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T04:33:52.023170Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

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verified fuzzy20
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2c0a9458-6fd5-4bac-abc7-d1a9a2599875 · outbound

This paper cites write newline.

Whitened CLIP as a Likelihood Surrogate of Images and Captions write newline

Reference 1

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Observation a4b813f8-5e53-43c0-ac1e-05a49490177e · outbound

This paper cites an unresolved cited work.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 2

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Observation 54b2d11d-d947-478e-8412-9d9b12a5b47b · outbound

This paper cites an unresolved cited work.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 3

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Observation ea6f08c5-ee87-47f3-97ce-e7112aadee00 · outbound

This paper cites Gpt-neo: Large scale autoregressive language modeling with mesh-tensorflow.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Gpt-neo: Large scale autoregressive language modeling with mesh-tensorflow

Reference 4

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Observation 680aab0f-6343-419b-930b-d02e51facaf5 · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Whitened CLIP as a Likelihood Surrogate of Images and Captions D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 5

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Observation f67cf553-fe3d-4544-89bf-bf87548cc2fd · outbound

This paper cites SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Model.

Whitened CLIP as a Likelihood Surrogate of Images and Captions SynArtifact: Classifying and Alleviating Artifacts in Synthetic Images via Vision-Language Model

Reference 6

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Observation ce7e5ed2-8b7d-4423-b7b6-c0682a596237 · outbound

This paper cites Embedding Geometries of Contrastive Language-Image Pre-Training.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Embedding Geometries of Contrastive Language-Image Pre-Training

Reference 7

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Observation 7755000a-6667-432e-b6b8-2aacbda7dd50 · outbound

This paper cites and Pearson, E.

Whitened CLIP as a Likelihood Surrogate of Images and Captions and Pearson, E

Reference 8

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Observation 18353692-d61f-428e-a370-f2ca0ab3b496 · outbound

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

Whitened CLIP as a Likelihood Surrogate of Images and Captions Imagenet: A large-scale hierarchical image database

Reference 9

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Observation f192eb3c-8ce5-4f25-85d0-7a23547ef6cd · outbound

This paper cites an unresolved cited work.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 10

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Observation 6afccaf3-c37e-46e7-9f43-77024692cc09 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Whitened CLIP as a Likelihood Surrogate of Images and Captions BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 11

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Observation f96faba4-68a2-47c8-bb43-5ead3ba30dd6 · outbound

This paper cites and Mordatch, I.

Whitened CLIP as a Likelihood Surrogate of Images and Captions and Mordatch, I

Reference 12

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Source-reported events for the cited work

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Observation cd193a06-7451-413c-b6a3-d1eaff471d0a · outbound

This paper cites Image inpainting: A review.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Image inpainting: A review

Reference 13

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Observation 6e5ff08b-9b4e-4815-8536-767a0daf467c · outbound

This paper cites Implicit diffusion models for continuous super-resolution.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Implicit diffusion models for continuous super-resolution

Reference 14

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Observation aca585c2-f6fb-400e-a4c7-4ae1e4c64082 · outbound

This paper cites and Geman, D.

Whitened CLIP as a Likelihood Surrogate of Images and Captions and Geman, D

Reference 15

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Observation fc693052-84d2-405c-af02-a5ff64858394 · outbound

This paper cites Openwebtext corpus.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Openwebtext corpus

Reference 16

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Observation 560ac1a3-63bf-471e-81f1-9e4f2f05efd1 · outbound

This paper cites Generative adversarial networks.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Generative adversarial networks

Reference 17

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Observation 7d5b9084-9af7-4d5f-a427-81c1d8eb6c12 · outbound

This paper cites S., and Sharma, A.

Whitened CLIP as a Likelihood Surrogate of Images and Captions S., and Sharma, A

Reference 18

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Observation 1a9db6ca-e910-4b26-81dd-c0c091fb8eb4 · outbound

This paper cites an unresolved cited work.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 19

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Observation 6b18316f-cdd3-4557-8c44-977467a32a21 · outbound

This paper cites Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

Reference 20

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This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

Whitened CLIP as a Likelihood Surrogate of Images and Captions The many faces of robustness: A critical analysis of out-of-distribution generalization

Reference 21

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This paper cites Natural adversarial examples.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Natural adversarial examples

Reference 22

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Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 23

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Observation e3e06eca-aeef-4a38-a0a3-ee0493c39ffb · outbound

This paper cites Denoising diffusion probabilistic models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Denoising diffusion probabilistic models

Reference 24

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Observation e7dd160f-057c-464b-b136-c5e137cee452 · outbound

This paper cites Framing image description as a ranking task: Data, models and evaluation metrics.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Framing image description as a ranking task: Data, models and evaluation metrics

Reference 25

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Observation 9c13272a-8818-4efd-8b4f-ff1f4b2ec19a · outbound

This paper cites Imagenet object localization challenge.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Imagenet object localization challenge

Reference 26

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This paper cites Imagic: Text-based real image editing with diffusion models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Imagic: Text-based real image editing with diffusion models

Reference 27

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This paper cites Auto-Encoding Variational Bayes.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Auto-Encoding Variational Bayes

Reference 28

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Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 29

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Observation c0c165a8-37ad-4168-a80c-a69032595ad7 · outbound

This paper cites Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models

Reference 30

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This paper cites Srdiff: Single image super-resolution with diffusion probabilistic models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Srdiff: Single image super-resolution with diffusion probabilistic models

Reference 31

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This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 32

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This paper cites W., Zhang, Y., Kwon, Y., Yeung, S., and Zou, J.

Whitened CLIP as a Likelihood Surrogate of Images and Captions W., Zhang, Y., Kwon, Y., Yeung, S., and Zou, J

Reference 33

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Reference 34

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Whitened CLIP as a Likelihood Surrogate of Images and Captions and Jupp, P

Reference 35

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Observation 362b6fea-76fb-4356-b452-c770e2ea845b · outbound

This paper cites ClipCap: CLIP Prefix for Image Captioning.

Whitened CLIP as a Likelihood Surrogate of Images and Captions ClipCap: CLIP Prefix for Image Captioning

Reference 36

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Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 37

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Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 38

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This paper cites Concentration of mass on convex bodies.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Concentration of mass on convex bodies

Reference 39

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This paper cites Language models are unsupervised multitask learners.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Language models are unsupervised multitask learners

Reference 40

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This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Whitened CLIP as a Likelihood Surrogate of Images and Captions W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 41

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This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 42

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Whitened CLIP as a Likelihood Surrogate of Images and Captions and Bialek, W

Reference 43

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This paper cites Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Two Effects, One Trigger: On the Modality Gap, Object Bias, and Information Imbalance in Contrastive Vision-Language Models

Reference 44

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Whitened CLIP as a Likelihood Surrogate of Images and Captions C., Bj \"o rkman, M., and Kragic, D

Reference 45

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This paper cites Denoising Diffusion Implicit Models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Denoising Diffusion Implicit Models

Reference 46

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This paper cites Deep learning on image denoising: An overview.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Deep learning on image denoising: An overview

Reference 47

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Observation cfec2dcf-6ddf-4109-a5c2-235a4c3f9783 · outbound

This paper cites High-Dimensional Probability: An Introduction with Applications in Data Science.

Whitened CLIP as a Likelihood Surrogate of Images and Captions High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:34:18.242503Z

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This paper cites GIT: A Generative Image-to-text Transformer for Vision and Language.

Whitened CLIP as a Likelihood Surrogate of Images and Captions GIT: A Generative Image-to-text Transformer for Vision and Language

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T22:34:17.967817Z

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Whitened CLIP as a Likelihood Surrogate of Images and Captions and Isola, P

Reference 50

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This paper cites Chatgpt or grammarly? evaluating chatgpt on grammatical error correction benchmark.

Whitened CLIP as a Likelihood Surrogate of Images and Captions Chatgpt or grammarly? evaluating chatgpt on grammatical error correction benchmark

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:34:18.219514Z

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Whitened CLIP as a Likelihood Surrogate of Images and Captions Unresolved cited work

Reference 52

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This paper cites OPT: Open Pre-trained Transformer Language Models.

Whitened CLIP as a Likelihood Surrogate of Images and Captions OPT: Open Pre-trained Transformer Language Models

Reference 53

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Whitened CLIP as a Likelihood Surrogate of Images and Captions and Weiss, Y

Reference 54

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Pith citing papers

Observation 226be0c5-61ab-4daa-b173-81220b474c88 · inbound

The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model cites this paper.

The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model Whitened CLIP as a Likelihood Surrogate of Images and Captions

Reference 2

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