Paper Citation Record · LEDGER

Distillation of a tractable model from the VQ-VAE

As of 21 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2509.01400.

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

pith.paper-citation-record.v1
2509.01400 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:41:34.300673Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:25:09.953112Z

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 exact1
verified fuzzy31
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 75f7cb3b-788c-4867-bfeb-ab3648d64c76 · outbound

This paper cites Semantic image synthesis with semantically coupled VQ - M odel, 2022.

Distillation of a tractable model from the VQ-VAE Semantic image synthesis with semantically coupled VQ - M odel, 2022

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.133265Z

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Observation 7156f61b-9298-4f7f-8ef1-ae7a4a22a37c · outbound

This paper cites 4m-21: An any-to-any vision model for tens of tasks and modalities.

Distillation of a tractable model from the VQ-VAE 4m-21: An any-to-any vision model for tens of tasks and modalities

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.116118Z

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Observation 08f0974d-aca2-47b1-af45-fd34ed282ff8 · outbound

This paper cites Probabilistic circuits: A unifying framework for tractable probabilistic models.

Distillation of a tractable model from the VQ-VAE Probabilistic circuits: A unifying framework for tractable probabilistic models

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.099716Z

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Observation f9e172bc-e141-4abd-a439-9d65176ea5c3 · outbound

This paper cites Correia, Gennaro Gala, Erik Quaeghebeur, Cassio De Campos, and Robert Peharz.

Distillation of a tractable model from the VQ-VAE Correia, Gennaro Gala, Erik Quaeghebeur, Cassio De Campos, and Robert Peharz

Reference 4

Resolution: verified exact; doi, observed 2026-08-05T12:41:34.355177Z

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Observation 77a56496-c1ce-4d7c-9ec1-308cbe3b3986 · outbound

This paper cites Efficient marginalization of discrete and structured latent variables via sparsity.

Distillation of a tractable model from the VQ-VAE Efficient marginalization of discrete and structured latent variables via sparsity

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.082535Z

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Observation 7890b03a-283a-4443-a44b-5d5a73316854 · outbound

This paper cites A knowledge compilation map.

Distillation of a tractable model from the VQ-VAE A knowledge compilation map

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.065250Z

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Observation 73d36d15-e584-46b3-8698-a0377f6fd48d · outbound

This paper cites Jukebox: A generative model for music, 2020.

Distillation of a tractable model from the VQ-VAE Jukebox: A generative model for music, 2020

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.047302Z

Source-reported events for the cited work

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Observation 9498e93a-144f-404c-9d1f-ea8d63b2fb70 · outbound

This paper cites Addressing index collapse of large-codebook speech tokenizer with dual-decoding product-quantized variational auto-encoder, 2024.

Distillation of a tractable model from the VQ-VAE Addressing index collapse of large-codebook speech tokenizer with dual-decoding product-quantized variational auto-encoder, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.030024Z

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Observation 169f69db-b7d3-4db8-a232-1f61ed4021c8 · outbound

This paper cites Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks, 2023.

Distillation of a tractable model from the VQ-VAE Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:35.010183Z

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Observation 9f92d579-ef0c-4250-aca9-50b22773d220 · outbound

This paper cites Adam: A method for stochastic optimization.

Distillation of a tractable model from the VQ-VAE Adam: A method for stochastic optimization

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.992408Z

Source-reported events for the cited work

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Observation dcd5a8a0-2328-4376-89ad-4339dd8b4599 · outbound

This paper cites Auto-encoding variational Bayes , 2022.

Distillation of a tractable model from the VQ-VAE Auto-encoding variational Bayes , 2022

Reference 11

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Observation aca0439d-85d0-4a43-b4dc-67179b3f8cca · outbound

This paper cites Lecun, L.

Distillation of a tractable model from the VQ-VAE Lecun, L

Reference 12

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Observation 234606ce-c018-42ce-96bc-259f23b33953 · outbound

This paper cites Scaling up probabilistic circuits by latent variable distillation.

Distillation of a tractable model from the VQ-VAE Scaling up probabilistic circuits by latent variable distillation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.957490Z

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Observation b5fb23f4-e64b-4b53-a08b-4c54563cf04c · outbound

This paper cites an unresolved cited work.

Distillation of a tractable model from the VQ-VAE Unresolved cited work

Reference 14

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Observation c290c71d-4752-4137-a932-fe64f9ebcaf5 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library, 2019.

Distillation of a tractable model from the VQ-VAE Pytorch: An imperative style, high-performance deep learning library, 2019

Reference 15

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Observation 65cd3540-d241-4ca2-baa2-866abf525e07 · outbound

This paper cites On the latent variable interpretation in sum-product networks.

Distillation of a tractable model from the VQ-VAE On the latent variable interpretation in sum-product networks

Reference 16

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Source-reported events for the cited work

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Observation 6e6fd9cc-5f9c-4f1d-8375-17a5f7d4c4ad · outbound

This paper cites Einsum networks: Fast and scalable learning of tractable probabilistic circuits.

Distillation of a tractable model from the VQ-VAE Einsum networks: Fast and scalable learning of tractable probabilistic circuits

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.884265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a6aaaa00-e4ce-4de7-8904-0e9cd34d799f · outbound

This paper cites Generating diverse structure for image inpainting with hierarchical VQ-VAE , 2021.

Distillation of a tractable model from the VQ-VAE Generating diverse structure for image inpainting with hierarchical VQ-VAE , 2021

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.869377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c0c8c17e-9c03-4077-9a02-8c39960d02c3 · outbound

This paper cites Sum-product networks: A new deep architecture, 2012.

Distillation of a tractable model from the VQ-VAE Sum-product networks: A new deep architecture, 2012

Reference 19

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Observation fc34a97b-432e-4634-a8e5-d4b14269600c · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.

Distillation of a tractable model from the VQ-VAE Stochastic backpropagation and approximate inference in deep generative models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.832071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7d1e1a3d-4444-4339-af8a-de5903963ddc · outbound

This paper cites Theory and experiments on vector quantized autoencoders, 2018.

Distillation of a tractable model from the VQ-VAE Theory and experiments on vector quantized autoencoders, 2018

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.817434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b7382722-af5c-4864-a014-59c57efc921a · outbound

This paper cites Generating high-quality and informative conversation responses with sequence-to-sequence models, 2017.

Distillation of a tractable model from the VQ-VAE Generating high-quality and informative conversation responses with sequence-to-sequence models, 2017

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.798441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5f1ec97a-c15d-4069-bf87-839615b1a4d9 · outbound

This paper cites Probabilistic flow circuits: Towards unified deep models for tractable probabilistic inference.

Distillation of a tractable model from the VQ-VAE Probabilistic flow circuits: Towards unified deep models for tractable probabilistic inference

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.776646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91f87d78-26e5-4aaa-a538-7d555afe1568 · outbound

This paper cites SQ-VAE : Variational Bayes on discrete representation with self-annealed stochastic quantization, 2022.

Distillation of a tractable model from the VQ-VAE SQ-VAE : Variational Bayes on discrete representation with self-annealed stochastic quantization, 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.753169Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75ba993d-83a9-4458-a0ec-5ddbfac7af48 · outbound

This paper cites A note on the evaluation of generative models, 2016.

Distillation of a tractable model from the VQ-VAE A note on the evaluation of generative models, 2016

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.732019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5020fa3a-7e9f-47f5-9c87-6de6a134885f · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction.

Distillation of a tractable model from the VQ-VAE Visual autoregressive modeling: Scalable image generation via next-scale prediction

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.711845Z

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Observation c6efaa3f-118e-494c-ab09-5be5efb75c93 · outbound

This paper cites Pixel recurrent neural networks, 2016 a.

Distillation of a tractable model from the VQ-VAE Pixel recurrent neural networks, 2016 a

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.684195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc8c4829-33d5-4bcb-85a4-23aec12285ec · outbound

This paper cites Conditional image generation with P ixel CNN decoders, 2016 b.

Distillation of a tractable model from the VQ-VAE Conditional image generation with P ixel CNN decoders, 2016 b

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.659204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3808e7ca-716f-4a37-a101-73993032396e · outbound

This paper cites Neural discrete representation learning.

Distillation of a tractable model from the VQ-VAE Neural discrete representation learning

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7234155b-a0e8-420d-a083-3d7b0f182e18 · outbound

This paper cites Tractable probabilistic models: Representations, algorithms, learning, and applications.

Distillation of a tractable model from the VQ-VAE Tractable probabilistic models: Representations, algorithms, learning, and applications

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.614797Z

Source-reported events for the cited work

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Observation 75b4af6a-99f0-4dcc-8d35-3e7972a6e721 · outbound

This paper cites Simplifying, regularizing and strengthening sum-product network structure learning.

Distillation of a tractable model from the VQ-VAE Simplifying, regularizing and strengthening sum-product network structure learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.593098Z

Source-reported events for the cited work

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Observation c9fbc7f5-20d6-41a5-8ded-61ae2df308ff · outbound

This paper cites Learning linear ranking functions for beam search with application to planning.

Distillation of a tractable model from the VQ-VAE Learning linear ranking functions for beam search with application to planning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.576762Z

Source-reported events for the cited work

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Observation 265e1faa-bb04-4507-9cf0-b342d5add23b · outbound

This paper cites V ideo GPT : Video generation using VQ-VAE and transformers, 2021.

Distillation of a tractable model from the VQ-VAE V ideo GPT : Video generation using VQ-VAE and transformers, 2021

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.556779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3b02180-806e-4052-980c-caefbce2fd1c · outbound

This paper cites Soundstream: An end-to-end neural audio codec, 2021.

Distillation of a tractable model from the VQ-VAE Soundstream: An end-to-end neural audio codec, 2021

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.540873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation aa8f7425-8e68-4af9-abb1-a768d9e1c91b · outbound

This paper cites A unified approach for learning the parameters of sum-product networks.

Distillation of a tractable model from the VQ-VAE A unified approach for learning the parameters of sum-product networks

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:41:34.525112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 28ce9940-5d74-4979-a075-3d8d24f9e0de · outbound

This paper cites Dolfing, Sameer Khurana, Tanel Alumäe, and Antoine Laurent.

Distillation of a tractable model from the VQ-VAE Dolfing, Sameer Khurana, Tanel Alumäe, and Antoine Laurent

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T12:41:34.300673Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4214421f-fe64-429b-bc0f-278feaeffdea · inbound

PreScience: A Dataset and Benchmark for Scientific Forecasting cites this paper.

PreScience: A Dataset and Benchmark for Scientific Forecasting Distillation of a tractable model from the VQ-VAE

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T21:25:09.953112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.