Paper Citation Record · LEDGER

Towards an Explainable Comparison and Alignment of Feature Embeddings

As of 8 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 1 inbound Pith citation observation for arXiv:2506.06231.

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

pith.paper-citation-record.v1
2506.06231 v3

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:05:39.610835Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T22:38:58.456728Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:27:09.499221Z

Reference resolution

71 of 71 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 56931454-58cb-45d2-9c40-70eac5a3ee59 · outbound

This paper cites write newline.

Towards an Explainable Comparison and Alignment of Feature Embeddings write newline

Reference 1

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Observation 72b7babf-8db5-466c-8837-71696bcd2e48 · outbound

This paper cites Fine-grained analysis of sentence embeddings using auxiliary prediction tasks.

Towards an Explainable Comparison and Alignment of Feature Embeddings Fine-grained analysis of sentence embeddings using auxiliary prediction tasks

Reference 2

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Observation 910ecde8-b4f4-4ebf-8984-efea7b666151 · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

Towards an Explainable Comparison and Alignment of Feature Embeddings Flamingo: a Visual Language Model for Few-Shot Learning

Reference 3

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Observation 8dbe173e-73cd-49bf-a77e-aa4d7a30371c · outbound

This paper cites Probing classifiers: Promises, shortcomings, and advances.

Towards an Explainable Comparison and Alignment of Feature Embeddings Probing classifiers: Promises, shortcomings, and advances

Reference 4

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This paper cites M., Baldock, R., Nanda, S., Oostermeijer, K., Cruz-Salinas, A.

Towards an Explainable Comparison and Alignment of Feature Embeddings M., Baldock, R., Nanda, S., Oostermeijer, K., Cruz-Salinas, A

Reference 5

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Observation a18e5b93-8885-4404-90b2-03490451264d · outbound

This paper cites Spectral clustering and kernel PCA are learning eigenfunctions , volume 1239.

Towards an Explainable Comparison and Alignment of Feature Embeddings Spectral clustering and kernel PCA are learning eigenfunctions , volume 1239

Reference 6

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Observation 61ad21af-32a0-4ad7-93ee-10468ee7a1ae · outbound

This paper cites Learning eigenfunctions of similarity: linking spectral clustering and kernel PCA.

Towards an Explainable Comparison and Alignment of Feature Embeddings Learning eigenfunctions of similarity: linking spectral clustering and kernel PCA

Reference 7

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Observation a927f8b0-9bbb-4490-b78f-912f27ac2436 · outbound

This paper cites Demystifying MMD GANs.

Towards an Explainable Comparison and Alignment of Feature Embeddings Demystifying MMD GANs

Reference 8

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This paper cites Embedding comparator: Visualizing differences in global structure and local neighborhoods via small multiples.

Towards an Explainable Comparison and Alignment of Feature Embeddings Embedding comparator: Visualizing differences in global structure and local neighborhoods via small multiples

Reference 9

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Observation a8344704-e700-4fc3-ba6f-d04fef5307d8 · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments, 2021.

Towards an Explainable Comparison and Alignment of Feature Embeddings Unsupervised learning of visual features by contrasting cluster assignments, 2021

Reference 10

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Observation d9eb70e8-7453-4ea8-ba7b-7f3dc8aa4d87 · outbound

This paper cites The Expressive Power of Word Embeddings.

Towards an Explainable Comparison and Alignment of Feature Embeddings The Expressive Power of Word Embeddings

Reference 11

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Towards an Explainable Comparison and Alignment of Feature Embeddings Unresolved cited work

Reference 12

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Observation 75eb1484-f03a-4a85-9e7a-022434021740 · outbound

This paper cites Evaluation of BERT and ALBERT sentence embedding performance on downstream NLP tasks.

Towards an Explainable Comparison and Alignment of Feature Embeddings Evaluation of BERT and ALBERT sentence embedding performance on downstream NLP tasks

Reference 13

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This paper cites StarGAN v2: Diverse image synthesis for multiple domains.

Towards an Explainable Comparison and Alignment of Feature Embeddings StarGAN v2: Diverse image synthesis for multiple domains

Reference 14

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Observation 2a4d3c2d-ce89-4ea3-948a-df9b60c48529 · outbound

This paper cites Analyzing transformers in embedding space.

Towards an Explainable Comparison and Alignment of Feature Embeddings Analyzing transformers in embedding space

Reference 15

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This paper cites B., Cheung, J.

Towards an Explainable Comparison and Alignment of Feature Embeddings B., Cheung, J

Reference 16

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Observation 0cc647f8-eb49-4d0b-98f3-6107904ef421 · outbound

This paper cites ImageNet: A Large-Scale Hierarchical Image Database.

Towards an Explainable Comparison and Alignment of Feature Embeddings ImageNet: A Large-Scale Hierarchical Image Database

Reference 17

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This paper cites and de Melo, G.

Towards an Explainable Comparison and Alignment of Feature Embeddings and de Melo, G

Reference 18

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Observation 20ca5fba-f526-49de-9e12-8f30b88c6a15 · outbound

This paper cites S im CSE : Simple contrastive learning of sentence embeddings.

Towards an Explainable Comparison and Alignment of Feature Embeddings S im CSE : Simple contrastive learning of sentence embeddings

Reference 19

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Towards an Explainable Comparison and Alignment of Feature Embeddings o m, N., and Sch \

Reference 20

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Towards an Explainable Comparison and Alignment of Feature Embeddings J., and Phillips, J

Reference 21

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Towards an Explainable Comparison and Alignment of Feature Embeddings V., Joulin, A., and Misra, I

Reference 22

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This paper cites Unsupervised alignment of embeddings with wasserstein procrustes.

Towards an Explainable Comparison and Alignment of Feature Embeddings Unsupervised alignment of embeddings with wasserstein procrustes

Reference 23

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This paper cites Recovering low-rank matrices from few coefficients in any basis.

Towards an Explainable Comparison and Alignment of Feature Embeddings Recovering low-rank matrices from few coefficients in any basis

Reference 24

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This paper cites Onellm: One framework to align all modalities with language.

Towards an Explainable Comparison and Alignment of Feature Embeddings Onellm: One framework to align all modalities with language

Reference 25

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

Towards an Explainable Comparison and Alignment of Feature Embeddings Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 26

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Towards an Explainable Comparison and Alignment of Feature Embeddings ImageWoof : a subset of 10 classes from imagenet that aren't so easy to classify, March 2019

Reference 27

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Towards an Explainable Comparison and Alignment of Feature Embeddings T., and Farnia, F

Reference 28

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Towards an Explainable Comparison and Alignment of Feature Embeddings Conditional Vendi Score: Prompt-Aware Diversity Evaluation for Generative AI Models and LLMs

Reference 29

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Towards an Explainable Comparison and Alignment of Feature Embeddings Feature likelihood score: Evaluating the generalization of generative models using samples

Reference 30

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Towards an Explainable Comparison and Alignment of Feature Embeddings A style-based generator architecture for generative adversarial networks

Reference 31

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Towards an Explainable Comparison and Alignment of Feature Embeddings The role of ImageNet classes in F r\'echet inception distance

Reference 33

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Towards an Explainable Comparison and Alignment of Feature Embeddings BLIP-2: bootstrapping language-image pre-training with frozen image encoders and large language models

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Towards an Explainable Comparison and Alignment of Feature Embeddings L., and Dollár, P

Reference 35

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Towards an Explainable Comparison and Alignment of Feature Embeddings Ro BERT a: A robustly optimized BERT pretraining approach, 2020

Reference 37

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Towards an Explainable Comparison and Alignment of Feature Embeddings Ovis: Structural Embedding Alignment for Multimodal Large Language Model

Reference 38

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Towards an Explainable Comparison and Alignment of Feature Embeddings Disentangling visual and written concepts in clip

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Towards an Explainable Comparison and Alignment of Feature Embeddings UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

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Towards an Explainable Comparison and Alignment of Feature Embeddings Pointer Sentinel Mixture Models

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Towards an Explainable Comparison and Alignment of Feature Embeddings MTEB : Massive text embedding benchmark

Reference 42

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Towards an Explainable Comparison and Alignment of Feature Embeddings On spectral clustering: Analysis and an algorithm

Reference 43

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Towards an Explainable Comparison and Alignment of Feature Embeddings Dinov2: Learning robust visual features without supervision, 2024

Reference 44

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Towards an Explainable Comparison and Alignment of Feature Embeddings Do Vendi Scores Converge with Finite Samples? Truncated Vendi Score for Finite-Sample Convergence Guarantees

Reference 45

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Towards an Explainable Comparison and Alignment of Feature Embeddings Towards a scalable reference-free evaluation of generative models

Reference 46

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Towards an Explainable Comparison and Alignment of Feature Embeddings Unresolved cited work

Reference 47

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Towards an Explainable Comparison and Alignment of Feature Embeddings Evaluation of sentence embeddings in downstream and linguistic probing tasks

Reference 48

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Towards an Explainable Comparison and Alignment of Feature Embeddings H., Zmigrod, R., Williams, A., and Cotterell, R

Reference 49

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Towards an Explainable Comparison and Alignment of Feature Embeddings W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., and Sutskever, I

Reference 50

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Towards an Explainable Comparison and Alignment of Feature Embeddings and Recht, B

Reference 51

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Towards an Explainable Comparison and Alignment of Feature Embeddings and Recht, B

Reference 52

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Towards an Explainable Comparison and Alignment of Feature Embeddings and Gurevych, I

Reference 53

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Towards an Explainable Comparison and Alignment of Feature Embeddings A primer in BERT ology: What we know about how BERT works

Reference 54

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Towards an Explainable Comparison and Alignment of Feature Embeddings Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models

Reference 55

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Towards an Explainable Comparison and Alignment of Feature Embeddings Word embedding evaluation in downstream tasks and semantic analogies

Reference 56

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Towards an Explainable Comparison and Alignment of Feature Embeddings Nonlinear Component Analysis as a Kernel Eigenvalue Problem

Reference 57

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Towards an Explainable Comparison and Alignment of Feature Embeddings and Markovitch, S

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.214340Z

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Reference 59

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Reference 60

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Towards an Explainable Comparison and Alignment of Feature Embeddings Rethinking the inception architecture for computer vision

Reference 61

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Reference 62

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Towards an Explainable Comparison and Alignment of Feature Embeddings and Hinton, G

Reference 63

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Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.158181Z

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Towards an Explainable Comparison and Alignment of Feature Embeddings Improving Text Embeddings with Large Language Models

Reference 65

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Towards an Explainable Comparison and Alignment of Feature Embeddings Understanding how dimension reduction tools work: An empirical approach to deciphering t-sne, umap, trimap, and pacmap for data visualization

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.148023Z

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Towards an Explainable Comparison and Alignment of Feature Embeddings Connecting multi-modal contrastive representations

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.137729Z

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Towards an Explainable Comparison and Alignment of Feature Embeddings Modalchorus: Visual probing and alignment of multi-modal embeddings via modal fusion map

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.127209Z

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Observation 72d1f194-5539-46e4-8128-9a778d8161c4 · outbound

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Towards an Explainable Comparison and Alignment of Feature Embeddings SEA: Supervised Embedding Alignment for Token-Level Visual-Textual Integration in MLLMs

Reference 69

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Towards an Explainable Comparison and Alignment of Feature Embeddings T., and Farnia, F

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T06:05:40.116502Z

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Observation 1795cc8f-9bc2-4889-af92-d254153c7d0e · outbound

This paper cites Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach.

Towards an Explainable Comparison and Alignment of Feature Embeddings Unveiling Differences in Generative Models: A Scalable Differential Clustering Approach

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T06:05:39.610835Z

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Pith citing papers

Observation 73a41106-a621-4877-ad9c-d3d2b66f23f9 · inbound

STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation cites this paper.

STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation Towards an Explainable Comparison and Alignment of Feature Embeddings

Reference 23

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