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Paper Citation Record · LEDGER

Distillation of a tractable model from the VQ-VAE

As of 10 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 2026-08-10T06:31:04.303077+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
  • metadata mismatch0

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.130580Z digest=sha256:e0a07d17ae9ea6d2e5d1b08170ce29dd7bc5de23cea8fe6f26fa837f53d1cf48

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.135420Z digest=sha256:48d0be6f45735521832e34de1d2f051ea031705403dbc2bc1b1b4fe13f8acb75

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.140275Z digest=sha256:51cfee7d69b594d88663c634798f1637b746ad5212cbb433f7d01b23a6777200

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.144714Z digest=sha256:45fe8a6582c1732e54289c507de6f6519c505614152a00efc31b3c831fbe1771

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.149836Z digest=sha256:a4a1ea0c702b24c1ea892b229f328660e9f057238db90d6acec888c94c2e568c

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.155000Z digest=sha256:5a4de7589fa25f7890c24f483d6f6c45672211e7a4be791d98be4db12635e49b

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.160433Z digest=sha256:55753293905e82c52d4020cf2172179d20748ee283a73ebe0dd6cf946e764dd0

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.165322Z digest=sha256:ce3a7534aea33c5086f685cf362e7534b2e4257af9d547aba3fb8c5170f2de2a

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.170007Z digest=sha256:5450d133d1f00400ea2da4e4d5f628be8a6d16acb28edbfa7a99a045d6160761

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.174815Z digest=sha256:916f2b8b2a2706d8e7077ed8460e9d26587f380ab9157a9e502ee5efee101a5d

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

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.179040Z digest=sha256:29fafc1b4a17662526d5775b37396a9f10e1a27368944bd05fa4789a1e321a5c

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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unresolved
no resolver link, observed 2026-08-05T12:41:34.183445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:41:34.183445Z digest=sha256:5575789c5fe0d5713b3c1fe674dc5392a0f52ee700b7843e116c2c0bd6c8f688

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.188482Z digest=sha256:e8d7d20c11d0cd08ef72506b38fb05ed77c60b37e1a7d1e98ecdbd2d00ca1604

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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unresolved
raw_fallback, observed 2026-08-05T12:41:34.941085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.192797Z digest=sha256:6a1dfd1e6c98588c1f0871dffe9dcf70d61eb21fa7f233084df9977efca39748

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

Resolution
unresolved
no resolver link, observed 2026-08-05T12:41:34.197489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:41:34.197489Z digest=sha256:967e4b7b2acf77014fba7b018aca5d42cdd8d22e51ab11230ce9ce44e934805c

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:41:34.906820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.202484Z digest=sha256:dbda46fa5562e9ffb45a374bbd1a9f71232350f0c7928efa09c79fd1d24153f0

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.211163Z digest=sha256:b5b72449ec7d879c5b6e22e2f46104a43b544762a0240aafe76dfd3411a09808

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.215700Z digest=sha256:f7676166415c96c22166c50038f4eee19271165c7fc2b1c2af19c80642a904aa

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:41:34.850854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.224533Z digest=sha256:1c2e7e48b2e37310fde760b565acbf6eda3359b01d7d39f699ab9790146b971c

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.229634Z digest=sha256:9890894239db531fb6989c925d245d1515138e01b8b9822b01d3a0869459a108

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.235045Z digest=sha256:f13168b5629eb4f744f3d294eff4f69e22c62be5c27db9e9e0ef5640f7946035

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.240256Z digest=sha256:0a25ce66a68abd4c6c423e241f9bc8cc6098c4d2e45bb3888db5f6f01622247d

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 2026-08-10T06:31:04.303077+00:00.

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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.249355Z digest=sha256:ef382ec9a4af74ef84fc306eda6f8aa34bb39edf6c0ed4c94f08687081460a6d

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.253695Z digest=sha256:9e6af0d59ed3e9f96784f591006f7d195a7910fb0bc1a582465ff61307252435

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.257967Z digest=sha256:f476d1330d254cbdca6faac764e36336bc1c576d3065b31c0c025f9ebb09e714

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.262096Z digest=sha256:8400f5c0b7afc52632d4c561d0962f61f7270aa4988d01156ada12478ec0a5bf

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.266053Z digest=sha256:47ab90f8b3ff8102e621b47c9124d44d0bb2b59f22e474a680c01011639dcc6d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T12:41:34.637444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.270886Z digest=sha256:f35696b7aa70327688114051b1e1b9db2d7e5ef4e5bf40e85d855f8d923548a0

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.275895Z digest=sha256:0f9891597857bf29da10fe497593cd18f04b317110d51fc08909d3448154c42a

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.279946Z digest=sha256:3fbe67d29fc34189e28c7591035c8ac77d227ba0cd125dc76ff6d924cd627d41

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.284172Z digest=sha256:4163f00a928f1309001ad47806a9490576df46e60c1c7edfa806953aff9d639c

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-05T12:41:34.288192Z digest=sha256:295792e6856adc584872765aaa309ba5b57a78d2cde5c2584d98ea7fdbdb7548

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 2026-08-10T06:31:04.303077+00:00.

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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

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source=arxiv_source observed=2026-08-05T12:41:34.296200Z digest=sha256:ccb4908ca37c0b3f22eb1f8226f92a594ea382ed0621f4666f9ac6864a112a06

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

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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

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