Paper Citation Record · LEDGER

Enhancing Interpretability of Sparse Latent Representations with Class Information

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2505.14476.

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

pith.paper-citation-record.v1
2505.14476 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:37:29.916762Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

26 of 26 outbound references displayed

verified exact2
verified fuzzy13
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 66ad711a-19d0-4606-b4b8-d513960d59e9 · outbound

This paper cites Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra.

Enhancing Interpretability of Sparse Latent Representations with Class Information Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.019491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0514baf6-8bc2-40d5-84f8-c198bd5c6fc4 · outbound

This paper cites Why should i trust you? explaining the predictions of any classifier.

Enhancing Interpretability of Sparse Latent Representations with Class Information Why should i trust you? explaining the predictions of any classifier

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.891860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation da3e4aa8-3793-4962-b3b1-60d48a5ddd45 · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Enhancing Interpretability of Sparse Latent Representations with Class Information A Unified Approach to Interpreting Model Predictions

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.186981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e9a571a-b465-4ab8-ac49-aef7026a1c96 · outbound

This paper cites The mnist database of handwritten digits.

Enhancing Interpretability of Sparse Latent Representations with Class Information The mnist database of handwritten digits

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.263941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4232d15-8697-4ee6-9cb6-21d9b9836a02 · outbound

This paper cites Auto-Encoding Variational Bayes.

Enhancing Interpretability of Sparse Latent Representations with Class Information Auto-Encoding Variational Bayes

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.374331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3986a56f-3918-4685-8258-fa5738ecde74 · outbound

This paper cites Generative adversarial networks.

Enhancing Interpretability of Sparse Latent Representations with Class Information Generative adversarial networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.461229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92b3a247-1dbc-4209-88e8-11290d6d1e30 · outbound

This paper cites Denoising diffusion probabilistic models.

Enhancing Interpretability of Sparse Latent Representations with Class Information Denoising diffusion probabilistic models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.576709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c219a0b0-68d9-413e-9aac-0c6f8b4dd643 · outbound

This paper cites Disentangling disentanglement in variational autoencoders.

Enhancing Interpretability of Sparse Latent Representations with Class Information Disentangling disentanglement in variational autoencoders

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.721083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cc84a63a-7138-4748-b456-694f9985a737 · outbound

This paper cites Understanding disentangling in $\beta$-VAE.

Enhancing Interpretability of Sparse Latent Representations with Class Information Understanding disentangling in $\beta$-VAE

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:27.785961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3178ce48-051f-4e7c-bbb1-f319c72b5e56 · outbound

This paper cites TC-VAE: Uncovering Out-of-Distribution Data Generative Factors.

Enhancing Interpretability of Sparse Latent Representations with Class Information TC-VAE: Uncovering Out-of-Distribution Data Generative Factors

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:37:30.379434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76aed60d-aeb6-42f9-bdfd-6a4e514f7ec4 · outbound

This paper cites Isolating sources of disentanglement in variational autoencoders.

Enhancing Interpretability of Sparse Latent Representations with Class Information Isolating sources of disentanglement in variational autoencoders

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.566041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96e386af-d8d6-4d77-b925-1efa87c4de7e · outbound

This paper cites Beta-vae: Learning basic visual concepts with a constrained variational framework.

Enhancing Interpretability of Sparse Latent Representations with Class Information Beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.430193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d6a80f32-094d-4b21-b903-db7ce269ccad · outbound

This paper cites Disentangling by factorizing.

Enhancing Interpretability of Sparse Latent Representations with Class Information Disentangling by factorizing

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.326207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ee711514-1724-4c06-a07e-e7026ae76f00 · outbound

This paper cites Discovering interpretable representations for both deep generative and discriminative models.

Enhancing Interpretability of Sparse Latent Representations with Class Information Discovering interpretable representations for both deep generative and discriminative models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.202791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4468b270-ff57-4dc4-bf07-95f5567bcdd1 · outbound

This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets.

Enhancing Interpretability of Sparse Latent Representations with Class Information Infogan: Interpretable representation learning by information maximizing generative adversarial nets

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:32.028950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ac854951-fa51-4bdd-b9c2-1f097c8ca9e2 · outbound

This paper cites Unsupervised discovery of interpretable directions in the gan latent space.

Enhancing Interpretability of Sparse Latent Representations with Class Information Unsupervised discovery of interpretable directions in the gan latent space

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:31.847606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b502a3b5-1044-4b01-a77e-fe8cabcb2f64 · outbound

This paper cites Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View.

Enhancing Interpretability of Sparse Latent Representations with Class Information Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:28.766246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86bac8bd-32b8-49c1-99ec-8c6caaedb039 · outbound

This paper cites Infogan-cr and modelcentrality: Self-supervised model training and selection for disentangling gans.

Enhancing Interpretability of Sparse Latent Representations with Class Information Infogan-cr and modelcentrality: Self-supervised model training and selection for disentangling gans

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:31.692233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df821e15-aa4d-4923-ac12-9a84e40519a0 · outbound

This paper cites GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images.

Enhancing Interpretability of Sparse Latent Representations with Class Information GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:37:30.222736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 15f9ac26-957b-4e8d-bc81-8644791fbc85 · outbound

This paper cites A disentangling invertible interpretation network for explaining latent representations.

Enhancing Interpretability of Sparse Latent Representations with Class Information A disentangling invertible interpretation network for explaining latent representations

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:31.472096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8b3cd198-c8de-467d-b2ae-e77729243606 · outbound

This paper cites DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models.

Enhancing Interpretability of Sparse Latent Representations with Class Information DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:29.328834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd1e3b77-05d9-4aab-86ca-5c37b930d26e · outbound

This paper cites Variational sparse coding, 2019.

Enhancing Interpretability of Sparse Latent Representations with Class Information Variational sparse coding, 2019

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:31.312456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5b60cfb5-2e29-4921-a55f-3f8f95f3b476 · outbound

This paper cites Barlow et al.

Enhancing Interpretability of Sparse Latent Representations with Class Information Barlow et al

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:31.139237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a44c331a-fc30-4e47-b116-a86627e9ac84 · outbound

This paper cites Types of dog ears, 2025.

Enhancing Interpretability of Sparse Latent Representations with Class Information Types of dog ears, 2025

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:37:30.971165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4e3d8aa6-7acc-4f2a-9b1c-dd61f36a9f94 · outbound

This paper cites an unresolved cited work.

Enhancing Interpretability of Sparse Latent Representations with Class Information Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:37:30.797390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79b25e2f-854f-4ed9-afb0-6c4eb4c5aaa5 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Enhancing Interpretability of Sparse Latent Representations with Class Information Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:29.916762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.