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Paper Citation Record · LEDGER

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows

As of 7 August 2026, this Paper Citation Record lists 99 of 99 outbound references and 2 inbound Pith citation observations for arXiv:2507.00425.

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

pith.paper-citation-record.v1
2507.00425 v1

Coverage vector

measured 99 of 99 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:24:31.103641Z

measured 101 of 101 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:25:46.516825Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T13:11:18.836504Z

Reference resolution

99 of 99 outbound references displayed

  • verified exact1
  • verified fuzzy44
  • unresolved54
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f2fddd25-f0bd-45f9-8951-370a27b3a0d0 · outbound

This paper cites Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg

Reference 1

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source=pdf_text observed=2026-08-06T21:24:18.517125Z digest=sha256:443eb34f8c0bd5937efddbc63cf06343c670bc182daa6febfdd30308cdae38eb

Observation 6a3b3690-7bd0-49ed-b742-12ac6eb17e6b · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-06T21:24:18.626638Z digest=sha256:628aac6417329757034469acd5e80e7cc9894506f9fd12864611242d529ea849

Observation 062ac775-8b32-4f7b-bfdd-7d9a8f6d476f · outbound

This paper cites Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio

Reference 3

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source=pdf_text observed=2026-08-06T21:24:18.750801Z digest=sha256:db7aabdf3e1314c44852c193593691b450fe4b3f4a23ca29cad0082ec9caedb0

Observation 27d05775-158b-4d20-abe8-9903137f4bde · outbound

This paper cites Large scale GAN training for high fidelity natural image synthesis.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Large scale GAN training for high fidelity natural image synthesis

Reference 4

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source=pdf_text observed=2026-08-06T21:24:18.879794Z digest=sha256:8769599c238e3e43e178d56952c43c588c75d235672500a99e03513726f6f496

Observation 54c07b95-dd09-44dc-b24f-ffc76cd05ef4 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-06T21:24:19.034654Z digest=sha256:63399ff917d6dce783bf98b6fd228484527e711560f62247245dd42d55fd4f74

Observation f8d4eaba-2cec-4494-b475-af028fcb2551 · outbound

This paper cites A continuous time framework for discrete denoising models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows A continuous time framework for discrete denoising models

Reference 6

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source=pdf_text observed=2026-08-06T21:24:19.153055Z digest=sha256:24eddc9f941df85653ea50879c7503cfef1c1a33521dd86abd4bf473cc23d1b1

Observation 8b1e66f6-e2b3-49cc-b5e8-ed9ec359a7c1 · outbound

This paper cites Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Reference 7

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source=pdf_text observed=2026-08-06T21:24:19.262729Z digest=sha256:12bac83ef1213b05ef671932a20fbde9e962912e127b2974d19113c0ad85b768

Observation b6f50b76-f21e-4dab-9a85-16498ef14d4e · outbound

This paper cites Block neural autoregressive flow.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Block neural autoregressive flow

Reference 8

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source=pdf_text observed=2026-08-06T21:24:19.393675Z digest=sha256:a353e14b5132d98dcb289b459fd21b454fa25afcfa13213be8cdba9905e9828f

Observation 086e2bb0-bb03-4bfa-9ef8-d57af6372af9 · outbound

This paper cites Go with the flow: Adaptive control for neural odes.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Go with the flow: Adaptive control for neural odes

Reference 9

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source=pdf_text observed=2026-08-06T21:24:19.544330Z digest=sha256:8e3701dd4b297c43e9fc3858e6ab11ef7fa8f25445072852e505b77ad64e5bb8

Observation 6e5a3bbf-71ad-4ca9-88f3-ab5493f6af70 · outbound

This paper cites Maximum-Likelihood Augmented Discrete Generative Adversarial Networks.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Maximum-Likelihood Augmented Discrete Generative Adversarial Networks

Reference 10

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source=pdf_text observed=2026-08-06T21:24:19.712510Z digest=sha256:c6c5901e19e3fef3e82eda6efdbcd470e7e873fd0b9827d8e9657c5724b6f723

Observation 309a4325-fc1d-4544-8f7a-fa1afc60e8b1 · outbound

This paper cites Neural ordinary differential equations.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Neural ordinary differential equations

Reference 11

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source=pdf_text observed=2026-08-06T21:24:19.830604Z digest=sha256:2a830360102a75dc6d16a2d7975315b7ff32513cb7bcfd613c6623010def0db1

Observation 0ea0788a-a8ed-4e18-b3d9-1b0fffa79840 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-06T21:24:19.972520Z digest=sha256:5e681fa7fe75dffdd8400eab8c4d3c49efa6f42c7cfac9e7b7992095d30fb79d

Observation e8a60a48-1745-4de4-9fec-4cfcdfa14271 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-06T21:24:20.112257Z digest=sha256:6956a8727492051e950bc2ea5bc99294cf12ccfc5fde1197e35801098a174b27

Observation 09a63e2d-9e6b-47a5-984c-eeb43562b583 · outbound

This paper cites Residual energy-based models for text generation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Residual energy-based models for text generation

Reference 14

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Observation 005188a3-8a11-44f2-80e8-d320a8777322 · outbound

This paper cites Continuous diffusion for categorical data.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Continuous diffusion for categorical data

Reference 15

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Observation 4cfa5053-daa2-4a97-aea6-60c5d5105272 · outbound

This paper cites Nice: Non-linear independent components estimation.International Conference on Learning Representations workshop Track, 2014.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Nice: Non-linear independent components estimation.International Conference on Learning Representations workshop Track, 2014

Reference 16

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Observation 94abeeef-82ae-46a8-bba5-24b660a8e2b8 · outbound

This paper cites Density estimation using real NVP.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Density estimation using real NVP

Reference 17

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Observation 0ae4c396-6839-4105-ab55-d0fda52ead8e · outbound

This paper cites Augmented neural odes.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Augmented neural odes

Reference 18

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Observation 086c5621-e87a-4233-8bba-3175aaa5239d · outbound

This paper cites Discrete Flow Matching.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Discrete Flow Matching

Reference 19

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source=pdf_text observed=2026-08-06T21:24:20.918552Z digest=sha256:e783244e4a2040770b190d87803cecf9b9b98b9f4ec18febb873b632c3dac823

Observation 71e467f7-f490-49db-acea-fd334bab6361 · outbound

This paper cites MADE: masked autoen- coder for distribution estimation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows MADE: masked autoen- coder for distribution estimation

Reference 20

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Observation cc6a270c-7881-435b-93ed-60a659dc8ec7 · outbound

This paper cites Better & Faster Large Language Models via Multi-token Prediction.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Better & Faster Large Language Models via Multi-token Prediction

Reference 21

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Observation 23398da7-329e-404a-b3cb-2eeb578dbe1a · outbound

This paper cites OpenWebText Corpus.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows OpenWebText Corpus

Reference 22

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Observation ffa8c04e-73b2-49df-8073-fb477dff8d5f · outbound

This paper cites Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sher- jil Ozair, Aaron C.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sher- jil Ozair, Aaron C

Reference 23

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source=pdf_text observed=2026-08-06T21:24:21.603338Z digest=sha256:82a0032eae595640eed0ea898295caf7408083ef3ff193f49b61854aa2b586d1

Observation 4334fb12-247d-45ff-ac92-ba7d93777c77 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-06T21:24:21.763105Z digest=sha256:f6f8b837a362489f1e3bc7bcf0bb2b1a977c1e510ae0ae38a35fb6334c3f321d

Observation ce4451ff-5e25-4708-bb98-07bb0011641b · outbound

This paper cites Bayesian Flow Networks.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Bayesian Flow Networks

Reference 25

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Observation e48f6a44-78b4-4603-bd40-ae439399b979 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 26

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Observation e27e4b0f-c070-4450-96b7-54794d6c9294 · outbound

This paper cites Hashimoto.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Hashimoto

Reference 27

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

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Observation e5de6df2-cdfb-4abf-b648-46647e83751b · outbound

This paper cites Deep residual learning for image recognition.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Deep residual learning for image recognition

Reference 28

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Observation a67c51fb-bbb7-4756-aff3-04746af96424 · outbound

This paper cites Flow++: Improving flow-based generative models with variational dequantization and architecture design.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Flow++: Improving flow-based generative models with variational dequantization and architecture design

Reference 29

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raw_fallback, observed 2026-08-06T21:24:39.084144Z

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.

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Observation d54c4a0e-d34c-49e9-aa75-19c3ba91dd49 · outbound

This paper cites Denoising diffusion probabilistic models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Denoising diffusion probabilistic models

Reference 30

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raw_fallback, observed 2026-08-06T21:24:38.962259Z

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.

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Observation 4bdcb3de-0b2e-451e-b131-39af3c87fd7d · outbound

This paper cites Argmax flows and multinomial diffusion: Learning categorical distributions.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Argmax flows and multinomial diffusion: Learning categorical distributions

Reference 31

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raw_fallback, observed 2026-08-06T21:24:38.880451Z

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

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Observation 2051028f-10b6-4d1d-9869-627748427eb0 · outbound

This paper cites Courville.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Courville

Reference 32

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raw_fallback, observed 2026-08-06T21:24:38.775251Z

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.

source=pdf_text observed=2026-08-06T21:24:22.795297Z digest=sha256:08da838ee7b6d3cd706f3bb6a46a147ee169f2e9275f3fe290457c673bd52542

Observation 849c85c2-82c1-411c-b56b-63a8d54196cd · outbound

This paper cites A stochastic estimator of the trace of the influence matrix for laplacian smoothing splines.Communications in Statistics-Simulation and Computation, 18(3):1059– 1076, 1989.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows A stochastic estimator of the trace of the influence matrix for laplacian smoothing splines.Communications in Statistics-Simulation and Computation, 18(3):1059– 1076, 1989

Reference 33

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Observation 31502675-18a8-4fef-913d-61c8b0188fa4 · outbound

This paper cites Scaling up gans for text-to-image synthesis.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Scaling up gans for text-to-image synthesis

Reference 34

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Observation 690125ae-1dfd-413e-99e2-98801c365039 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows A style-based generator architecture for generative adversarial networks

Reference 35

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Observation 16b3e351-6dff-4e73-bfc6-1616aa989174 · outbound

This paper cites Maximum likelihood training of implicit nonlinear diffusion model.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Maximum likelihood training of implicit nonlinear diffusion model

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:38.672706Z

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.

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Observation aa04c4dc-31e0-4443-9fa5-bf2be37142bf · outbound

This paper cites Kingma and Prafulla Dhariwal.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Kingma and Prafulla Dhariwal

Reference 37

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raw_fallback, observed 2026-08-06T21:24:38.584270Z

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.

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Observation a63bb553-9c4a-4605-8e18-bf93300e7466 · outbound

This paper cites Auto-Encoding Variational Bayes.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Auto-Encoding Variational Bayes

Reference 38

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source=pdf_text observed=2026-08-06T21:24:23.543216Z digest=sha256:319aa3ba6f7dd204aef6394298aadee138ffbe38d39d3c5beb0574c9df6120c4

Observation e374a903-e417-410c-af38-4f60c90d9b60 · outbound

This paper cites Improved variational inference with inverse autoregressive flow.Advances in neural information processing systems, 29, 2016.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Improved variational inference with inverse autoregressive flow.Advances in neural information processing systems, 29, 2016

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source=pdf_text observed=2026-08-06T21:24:23.695854Z digest=sha256:c1ff37252589165dd4de9f3720652f23d7cc7a181e917064a9962cc55e7f06af

Observation 0f052004-1fac-4acf-b6ea-8848b16ec03a · outbound

This paper cites Hashimoto.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Hashimoto

Reference 40

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raw_fallback, observed 2026-08-06T21:24:38.413654Z

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.

source=pdf_text observed=2026-08-06T21:24:23.819363Z digest=sha256:8ecf18de72625b7bf5fad3203be5a0b238194e42f819a6050e58818ccf53d27f

Observation f51e0ac8-b7e9-4549-b6e3-51622a79ea16 · outbound

This paper cites Categorical normalizing flows via continuous transforma- tions.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Categorical normalizing flows via continuous transforma- tions

Reference 41

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raw_fallback, observed 2026-08-06T21:24:38.307007Z

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

source=pdf_text observed=2026-08-06T21:24:23.963905Z digest=sha256:f1d76bffba0e06ec79923736d014d62d9c7ff4e7337cfd0dc59d1265f6d7f794

Observation 1d2c0ccc-379e-4446-a02b-1c4b34831820 · outbound

This paper cites DeepSeek-V3 Technical Report.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows DeepSeek-V3 Technical Report

Reference 42

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source=pdf_text observed=2026-08-06T21:24:24.076955Z digest=sha256:6cb7d3c92c37af6be57f1fc28f522288ef74d5dbac3e38b6ee19c93f4e52f35f

Observation a017b8c1-e32f-47cd-bcc1-d995f0dc0f6d · outbound

This paper cites Theodorou.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Theodorou

Reference 43

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raw_fallback, observed 2026-08-06T21:24:38.201730Z

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.

source=pdf_text observed=2026-08-06T21:24:24.163984Z digest=sha256:5838a0fec318afb4e197414da2692d1135b5a4fda0d99d565122283cf19051e8

Observation eb42c7c5-c93e-4283-8373-52ca68bf8cc1 · outbound

This paper cites Think While You Generate: Discrete Diffusion with Planned Denoising.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Think While You Generate: Discrete Diffusion with Planned Denoising

Reference 44

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source=pdf_text observed=2026-08-06T21:24:24.305000Z digest=sha256:2c60d7cf967a922b7a35ea358cd0c9c26640832d8ece55bfbcb705a061a2cc82

Observation ed932051-8fe6-4ba4-aa35-656bbeb37eda · outbound

This paper cites Discrete diffusion modeling by estimat- ing the ratios of the data distribution.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Discrete diffusion modeling by estimat- ing the ratios of the data distribution

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:38.028601Z

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.

source=pdf_text observed=2026-08-06T21:24:24.442164Z digest=sha256:e9d376cfe79978d3a85543593b374bced06f51fcaf4459f00b52e97c08d20157

Observation 7724c9a9-655e-470f-a906-0fa7f60ae3d2 · outbound

This paper cites Maximum likelihood training for score-based diffusion odes by high order denoising score matching.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Maximum likelihood training for score-based diffusion odes by high order denoising score matching

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:37.883614Z

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.

source=pdf_text observed=2026-08-06T21:24:24.592456Z digest=sha256:c104a09f206b4e69404970175b445cc4fb8e99487b4573720e145bfd7197e7c6

Observation cdc0e2a7-5680-47b8-a959-a4cea2490e2b · outbound

This paper cites text8 Corpus.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows text8 Corpus

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:37.753882Z

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.

source=pdf_text observed=2026-08-06T21:24:24.731868Z digest=sha256:8fc84f3b4afde4fa1968f8b0e0cb63239ebf99b9b5a804a6579707648a1a682f

Observation 6b2f0384-b5c1-4e2b-8a7b-b61800d83c4e · outbound

This paper cites Concrete score match- ing: Generalized score matching for discrete data.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Concrete score match- ing: Generalized score matching for discrete data

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:37.665125Z

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.

source=pdf_text observed=2026-08-06T21:24:24.899102Z digest=sha256:11bacea6f701bbc3c6759afdd1392bba0811453263a9c1e9bde6863b513eaf4c

Observation 4f6484aa-eee3-4529-864b-ee9a84821591 · outbound

This paper cites Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data

Reference 49

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source=pdf_text observed=2026-08-06T21:24:25.021132Z digest=sha256:ded478690530f8193f25ba89d95a03005ec782c71a8028edda9015de7da0b5ad

Observation 8b5fe5ce-ba7d-41fb-8ead-6d068fd555f6 · outbound

This paper cites Masked autoregressive flow for density estimation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Masked autoregressive flow for density estimation

Reference 50

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:37.536532Z

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.

source=pdf_text observed=2026-08-06T21:24:25.126688Z digest=sha256:08759007af587e81c373604bc712687ab3fbcb504c236aefb02578cead5fc573

Observation 849aecf3-f3da-447e-b198-5efab2ff8b64 · outbound

This paper cites Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan

Reference 51

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raw_fallback, observed 2026-08-06T21:24:37.401967Z

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.

source=pdf_text observed=2026-08-06T21:24:25.278502Z digest=sha256:c75d0f1865b6998ab9929a19448da2daf7d93b6a6005fcfafbae8d17c3a7de0c

Observation 7495996a-bb6e-4d56-b59e-0e23dca13292 · outbound

This paper cites Transformer Neural Autoregressive Flows.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Transformer Neural Autoregressive Flows

Reference 52

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verified exact
local_arxiv, observed 2026-08-06T21:24:31.285471Z

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.

source=pdf_text observed=2026-08-06T21:24:25.397582Z digest=sha256:8990f41c99bf5ef99871cfec4527b8a58eff290844fef43ba6f1b32b6c330773

Observation b8d8147c-7f3d-4b0e-abb2-2b6200e22a15 · outbound

This paper cites Sdxl: Improving latent diffusion models for high-resolution image synthesis.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Sdxl: Improving latent diffusion models for high-resolution image synthesis

Reference 53

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source=pdf_text observed=2026-08-06T21:24:25.524981Z digest=sha256:a7d6e0235d80c7abdfd69b16aa9aed84c178e1eeda86ad7995945511d4e866ab

Observation 8c7b1d64-3438-43fe-b656-7fc52da779b7 · outbound

This paper cites Routledge, 2018.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Routledge, 2018

Reference 54

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source=pdf_text observed=2026-08-06T21:24:25.662684Z digest=sha256:086dccd5b0a955cba3667ff7ce39a708cca32b4cc1533aec420613a238ee5e8c

Observation 9d6ba36d-65ee-49ec-a4d1-50fd1ca2a2e6 · outbound

This paper cites Remarks on a multivariate transformation.The annals of mathematical statistics, 23(3):470–472, 1952.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Remarks on a multivariate transformation.The annals of mathematical statistics, 23(3):470–472, 1952

Reference 55

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raw_fallback, observed 2026-08-06T21:24:37.256059Z

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.

source=pdf_text observed=2026-08-06T21:24:25.776995Z digest=sha256:895fdbd2b18df7ad72dde8abe46e4d3c95b5e3a4647511a0e839a5ca95d5de52

Observation f836a96f-dca2-4bc4-ade2-12ddde48a7ac · outbound

This paper cites Simple and Effective Masked Diffusion Language Models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Simple and Effective Masked Diffusion Language Models

Reference 56

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source=pdf_text observed=2026-08-06T21:24:25.971758Z digest=sha256:fc2ff58b16bc4b2e582b40f148e9f03080f7c79311136679b485487e4f331fc4

Observation f451da14-d9b6-477f-b4cc-7de2d94a0f88 · outbound

This paper cites Step-unrolled denoising autoencoders for text generation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Step-unrolled denoising autoencoders for text generation

Reference 57

Resolution
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raw_fallback, observed 2026-08-06T21:24:37.112887Z

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.

source=pdf_text observed=2026-08-06T21:24:26.132697Z digest=sha256:43a4cd7d373bf092b308f18f0eee686a45ccdb2d10c308f9ffd3d78c5058278e

Observation 5a9e5645-cedb-40ae-b06b-1eea0d305415 · outbound

This paper cites Simplified and Generalized Masked Diffusion for Discrete Data.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Simplified and Generalized Masked Diffusion for Discrete Data

Reference 58

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source=pdf_text observed=2026-08-06T21:24:26.336851Z digest=sha256:6164a9970a0fa0ebee7a7172a51355a4071236b176a93f3cd6b332ee527b004b

Observation 5a540c5d-7964-41fe-98e3-306f14c8dd89 · outbound

This paper cites Training and inference on any-order autore- gressive models the right way.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Training and inference on any-order autore- gressive models the right way

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.820790Z

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.

source=pdf_text observed=2026-08-06T21:24:26.444783Z digest=sha256:b00b083fbc31172c97cda00d6fd902497cf5c561d173e0e748f67592a4b12e23

Observation 2af32222-26f9-4143-8f40-436fd68ec888 · outbound

This paper cites Weiss, Niru Maheswaranathan, and Surya Ganguli.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Weiss, Niru Maheswaranathan, and Surya Ganguli

Reference 60

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.664468Z

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.

source=pdf_text observed=2026-08-06T21:24:26.554940Z digest=sha256:88683861d7eedce39be64979944a50aafea7786267b9e9e4358b02de97c67929

Observation 5ef5208d-0e6e-4159-b044-2783dea51834 · outbound

This paper cites Maximum likelihood training of score-based diffusion models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Maximum likelihood training of score-based diffusion models

Reference 61

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.525870Z

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.

source=pdf_text observed=2026-08-06T21:24:26.653129Z digest=sha256:bd5cb593200056c3b8e8ac46b8e4022d09b5b57a9b9e341738f9553c7fbc2605

Observation ff5c641d-2f03-48e9-b49a-6db8b163b3fd · outbound

This paper cites Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole

Reference 62

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.359511Z

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.

source=pdf_text observed=2026-08-06T21:24:26.751868Z digest=sha256:2957089a3c74ab49bdc20ac86034156340c2ddd6b849f25a0eaf750445f5022c

Observation 5b1b0a7a-e709-436d-97d7-37ee9f471161 · outbound

This paper cites f-VAEs: Improve VAEs with Conditional Flows.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows f-VAEs: Improve VAEs with Conditional Flows

Reference 63

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source=pdf_text observed=2026-08-06T21:24:26.859944Z digest=sha256:0de5a6e39fc49b4b51a76c10a6dedba3d1f6198f0e2862312b1cb9e1b3ba804a

Observation 37c59f73-e769-4915-9b45-eb3129f0fc1e · outbound

This paper cites Score-based continuous- time discrete diffusion models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Score-based continuous- time discrete diffusion models

Reference 64

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.233653Z

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.

source=pdf_text observed=2026-08-06T21:24:26.980251Z digest=sha256:b8f0b9b25898e78b7523e3637f1a74fe9cf3a5ca09e808d224fb9bf8d23cd101

Observation 00c86ea8-5aa4-4d62-b6b1-835356c12d54 · outbound

This paper cites Neural discrete representation learning.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Neural discrete representation learning

Reference 65

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:36.073758Z

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.

source=pdf_text observed=2026-08-06T21:24:27.129634Z digest=sha256:c35fef9f3e867589363b063ddbc4e4125e769d80f58b647c19febee1bda264b6

Observation 4ee3fd38-4717-416d-a654-b98c2220431f · outbound

This paper cites Attention is all you need.(nips), 2017.Advances in neural information processing systems, 30, 2017.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Attention is all you need.(nips), 2017.Advances in neural information processing systems, 30, 2017

Reference 66

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raw_fallback, observed 2026-08-06T21:24:35.969991Z

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.

source=pdf_text observed=2026-08-06T21:24:27.255123Z digest=sha256:b49e0850b08b2473e19f669ba0fadb46ea0585a22c633ed5564fb40c03c644ff

Observation 50d0678d-d33f-461f-81a9-6ef99bfce36a · outbound

This paper cites Digress: Discrete denoising diffusion for graph generation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Digress: Discrete denoising diffusion for graph generation

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:35.825933Z

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.

source=pdf_text observed=2026-08-06T21:24:27.408607Z digest=sha256:753a24d72969b428f56f9c491053af62a1ae73e25e5a31f8ea590f2fb0709cfe

Observation f6830c3b-aa4c-48d5-a0e0-ab99f666a84c · outbound

This paper cites Stabilizing Generative Adversarial Networks: A Survey.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Stabilizing Generative Adversarial Networks: A Survey

Reference 68

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no resolver link, observed 2026-08-06T21:24:27.540596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:27.540596Z digest=sha256:ad13fe6b716a797a33f20a6c43f78d3ec4d760e0c5fa3f400f8c5fa58f7b6a25

Observation 42388cbf-e9c9-40d5-9e64-c420b334bb83 · outbound

This paper cites Energy-Based Diffusion Language Models for Text Generation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Energy-Based Diffusion Language Models for Text Generation

Reference 69

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no resolver link, observed 2026-08-06T21:24:27.645274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:27.645274Z digest=sha256:40a83cf9820125c4fed9077efa5903edaa8c39fa0651a4d9f6f1ed932aecebfd

Observation 896146bb-a990-4ff3-954e-093d5e1bf887 · outbound

This paper cites Seqgan: Sequence generative adversarial nets with policy gradient.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Seqgan: Sequence generative adversarial nets with policy gradient

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:35.693100Z

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.

source=pdf_text observed=2026-08-06T21:24:27.750307Z digest=sha256:56b11ab49f218f4d12a7e7fa945bc6004944affd918f50eb17fee6e33bb6313b

Observation f037e215-73a4-4023-96bd-0aa1bd80e113 · outbound

This paper cites Normalizing Flows are Capable Generative Models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Normalizing Flows are Capable Generative Models

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:27.887508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:27.887508Z digest=sha256:87c315fd54beddddbac348449a2a3bb789d24a9e4d1a7b85baf773987b9f3265

Observation bb8d1794-512e-4942-9a03-9db74aa55b03 · outbound

This paper cites Learning structured latent factors from dependent data:a generative model framework from information-theoretic perspective.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Learning structured latent factors from dependent data:a generative model framework from information-theoretic perspective

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:35.517612Z

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.

source=pdf_text observed=2026-08-06T21:24:28.049428Z digest=sha256:8bba36971b6bb3fd416a504622637b6064ebc087be7f49e496329f47cbbe373f

Observation 97d4a4c3-4f93-4f0b-9d2a-b0d548dddceb · outbound

This paper cites Susskind.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Susskind

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:35.305356Z

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.

source=pdf_text observed=2026-08-06T21:24:28.174819Z digest=sha256:98d79cee587239205d1e09b5919d765cf4864dc48d5f164d57a38cd0700b2f68

Observation 8a83834a-2085-4d31-8f56-d45a618a08a3 · outbound

This paper cites Robust and controllable object-centric learning through energy-based models.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Robust and controllable object-centric learning through energy-based models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:34.970344Z

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.

source=pdf_text observed=2026-08-06T21:24:28.377318Z digest=sha256:4efb292b01dc2598fb3606408f15e14cb2f9108cfeb249d6794c96679846f1cb

Observation f8766bd6-628f-49a2-88d6-80225ea14b67 · outbound

This paper cites Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion

Reference 75

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unresolved
no resolver link, observed 2026-08-06T21:24:28.479602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:28.479602Z digest=sha256:fdc33d333d5892c5f84c40b8b4433293463935ac6d07cda1b38b8fa710cf8f2e

Observation 03194e4e-0677-4876-a857-1317bc0334e8 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 76

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unresolved
raw_fallback, observed 2026-08-06T21:24:35.131890Z

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.

source=pdf_text observed=2026-08-06T21:24:28.272137Z digest=sha256:b60f57fdd80015949e6853c8f0ac7434b9bc011eca21f338ad979e5bd801ddc7

Observation 3ec40076-0fcc-49f9-9515-e3d34cb97e67 · outbound

This paper cites A Reparameterized Discrete Diffusion Model for Text Generation.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows A Reparameterized Discrete Diffusion Model for Text Generation

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-06T21:24:28.657707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:28.657707Z digest=sha256:1b9b08a651b7fd467fae3a8b660b50fe5366b10d8ca7a8f6578f23f6c6bebc7c

Observation c239c8f5-0ac0-4a6f-b97a-2c098841553c · outbound

This paper cites Open-sora: Democratizing efficient video production for all,.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Open-sora: Democratizing efficient video production for all,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:34.693564Z

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.

source=pdf_text observed=2026-08-06T21:24:28.784523Z digest=sha256:990332f3086f00baa4aa6b68d9bb0bc3eb16b6d7f1f5f7b3ee22690ab2194a00

Observation 4b6aff9f-7bf1-47a9-804d-95f629f3a730 · outbound

This paper cites Perceptual generative autoencoders.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Perceptual generative autoencoders

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:34.847450Z

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.

source=pdf_text observed=2026-08-06T21:24:28.561659Z digest=sha256:becf35f2c3a61101f3f9e3c5df4e8f34b0f4a4d484be81e8fe1040da87617428

Observation 131cc242-056c-49f6-9589-b975269b4cde · outbound

This paper cites Ziegler and Alexander M.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Ziegler and Alexander M

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:34.047296Z

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.

source=pdf_text observed=2026-08-06T21:24:29.181054Z digest=sha256:1bb9131e462004bcecfc3afb1fa25fa4971890f7c6c8e4cd86b3445753911a89

Observation 0d70c588-425a-47ef-8d40-91e3a5fbf0ee · outbound

This paper cites Dvornek, Sekhar Tatikonda, and James S.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Dvornek, Sekhar Tatikonda, and James S

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:34.448336Z

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.

source=pdf_text observed=2026-08-06T21:24:28.998577Z digest=sha256:49125b15f29040095046114d53990d1cf51817ff5a77f8e9dad57958dc594db3

Observation 19e313f9-339c-4bf1-acd3-746fc6c6beef · outbound

This paper cites Differentiating ycdf = Φ(u t,i) with respect to ut,i yields dycdf dut,i = N(u t,i; 0,1), where N(u t,i; 0,1) is the PDF of the standard normal distribution.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Differentiating ycdf = Φ(u t,i) with respect to ut,i yields dycdf dut,i = N(u t,i; 0,1), where N(u t,i; 0,1) is the PDF of the standard normal distribution

Reference 86

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:33.861841Z

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.

source=pdf_text observed=2026-08-06T21:24:29.274671Z digest=sha256:49476f262cfc91cb4d07aa6e6682f35ef61fe9ddd892c0540874c130d5d16852

Observation 6035bc44-16c1-4295-ae37-8e21387d3939 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 87

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unresolved
raw_fallback, observed 2026-08-06T21:24:33.640939Z

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.

source=pdf_text observed=2026-08-06T21:24:29.383326Z digest=sha256:d1a72399a190de8b363ae6c3735d238e09907695666f13cabb7d7afec0a7dbd2

Observation 1d57d8f7-2173-48d3-9e2a-3e20c38c166f · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 88

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:33.443716Z

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.

source=pdf_text observed=2026-08-06T21:24:29.497339Z digest=sha256:b354e9e3b04eb46968a6d287bba33bda96ac9ee9c99da5e044406a2843e75770

Observation 486e68a3-d494-4ba0-b495-a48a1a3be176 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 89

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:33.261085Z

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.

source=pdf_text observed=2026-08-06T21:24:29.633740Z digest=sha256:6da68150ba6afc4f883ab50e7e37943c4ca1d722afc565f12609563e742cb2a7

Observation 99610cad-4d44-41a4-8a7f-4160086435b6 · outbound

This paper cites For a given component k, z follows a single multivariate Gaussian distribution N(m k, σ2 kId).

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows For a given component k, z follows a single multivariate Gaussian distribution N(m k, σ2 kId)

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:33.082583Z

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.

source=pdf_text observed=2026-08-06T21:24:29.754262Z digest=sha256:f77e8d283cc9b32ae9d5aee20aa4d10726a92040ba7e8fc21f10b10f6a101f08

Observation 84c0d40b-d689-4a71-80c7-6235cc1c7586 · outbound

This paper cites We denote this by α(i) k (z<i) and compute it using Bayes’ rule: P(K=k|z <i) = p(z<i|K=k)P(K=k) p(z<i) = p(z<i|K=k)P(K=k)PV j=1 p(z<i|K=j)P(K=j).

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows We denote this by α(i) k (z<i) and compute it using Bayes’ rule: P(K=k|z <i) = p(z<i|K=k)P(K=k) p(z<i) = p(z<i|K=k)P(K=k)PV j=1 p(z<i|K=j)P(K=j)

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:32.875696Z

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.

source=pdf_text observed=2026-08-06T21:24:29.904072Z digest=sha256:8fb78ce339a9e44c13f3559c37cc0347a14fb214faa764947aaf5dab8686c838

Observation d5c725e3-6878-4ee7-be37-c645f228c300 · outbound

This paper cites This corresponds to minimizingKL(q in∥pmodel).

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows This corresponds to minimizingKL(q in∥pmodel)

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:32.684737Z

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.

source=pdf_text observed=2026-08-06T21:24:30.126211Z digest=sha256:574164276e180493fb9c2223d945e52d06eb797f8654067ca91fc4869d25090e

Observation 8d09be4c-dcc4-4e75-8397-6d1a51f6706d · outbound

This paper cites Flexible Patch Size.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Flexible Patch Size

Reference 93

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verified fuzzy
raw_fallback, observed 2026-08-06T21:24:32.545944Z

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.

source=pdf_text observed=2026-08-06T21:24:30.338090Z digest=sha256:eb7169bbe332194e093e38bfc8b7e320a5e0fb22c61b90d01fa2f72b93032548

Observation 8f6282bb-b67a-4d1c-bdb8-b43ccdcfc352 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 94

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unresolved
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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.

source=pdf_text observed=2026-08-06T21:24:30.496303Z digest=sha256:4820ee63890da99a69dd6d86be330903fcff6e67ecc4d82f79bbb5f15049f4bb

Observation e292e8de-8de5-4a3e-8bea-35eb22c245e6 · outbound

This paper cites ,zt−1)will converge to(µ x1 ,.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows ,zt−1)will converge to(µ x1 ,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:32.270096Z

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.

source=pdf_text observed=2026-08-06T21:24:30.700258Z digest=sha256:d215ba01ccf2f988881add0c468225c3b2c2a01f7e3ffeb5fe6dc9fc4e9b11c4

Observation 8b85e9ee-8bcb-46d6-8b61-1c8fbaa62efc · outbound

This paper cites equation 71) evaluated at zt ≈µ xt will behave as follows: If µk are distinct, then for zt ≈µ xt, Nxt (zt) will be large, while Nj(zt) for j̸=x t will be very small.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows equation 71) evaluated at zt ≈µ xt will behave as follows: If µk are distinct, then for zt ≈µ xt, Nxt (zt) will be large, while Nj(zt) for j̸=x t will be very small

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:32.115556Z

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.

source=pdf_text observed=2026-08-06T21:24:30.852858Z digest=sha256:2daf993867bd27343178984303026d71a9ed49f551dfe0d79dc910f2bcde1153

Observation 1b6365d5-24f3-4594-a1a7-51bd18d552d8 · outbound

This paper cites RealNVP [17] built upon this by introducing scaling and shifting operations, thereby increasing model flexibility.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows RealNVP [17] built upon this by introducing scaling and shifting operations, thereby increasing model flexibility

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:31.979099Z

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.

source=pdf_text observed=2026-08-06T21:24:31.036828Z digest=sha256:70e952a6efc11cc684f5730cfd07dd01c098c6844729ab5f19d52ffa3b505c3c

Observation a42cfea9-05fc-4fc0-bf5f-fba8575da275 · outbound

This paper cites Other prominent generative models include Variational Autoencoders (V AEs) [38] and Generative Adversarial Networks (GANs) [23].

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Other prominent generative models include Variational Autoencoders (V AEs) [38] and Generative Adversarial Networks (GANs) [23]

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:31.830540Z

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.

source=pdf_text observed=2026-08-06T21:24:31.083975Z digest=sha256:b715668e8b164441a665537002abf8aa8d7a5d4fe22e8237e31c6592441711fc

Observation fe394e88-a1d0-4d1f-ae90-a37efe35185c · outbound

This paper cites analog bits,.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows analog bits,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:24:31.641308Z

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.

source=pdf_text observed=2026-08-06T21:24:31.103641Z digest=sha256:47ac970c99cdf931acc042106315b75b003ad752ad25041627b8c1da5742e907

Observation 525f75c3-7a9a-4953-948d-083700b9c0bb · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 2015

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unresolved
no resolver link, observed 2026-08-06T21:24:21.223874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:21.223874Z digest=sha256:b3e127963540050f5f368c4551935c67160a00bf22280c2d3236839a37d8ad37

Observation 74109a62-ed49-49e6-b98c-111d29dd0967 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 2021

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:34.294408Z

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.

source=pdf_text observed=2026-08-06T21:24:29.094673Z digest=sha256:8b4ba2b5f3a6371173fba06b8fd3d51fafadef6744bad5a06ab9dcfd7682b353

Observation 50485a9d-ab1f-4388-93fd-7043c9f27feb · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:36.970843Z

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.

source=pdf_text observed=2026-08-06T21:24:26.242084Z digest=sha256:6ec6ab47e2172e047e7e5647dc6abee6826335c77aa751e9cd465c35806ab92a

Observation 164476e6-6f8e-4954-a05f-e9a1575f0201 · outbound

This paper cites an unresolved cited work.

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows Unresolved cited work

Reference 2024

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:34.593796Z

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.

source=pdf_text observed=2026-08-06T21:24:28.895823Z digest=sha256:a087e65bef9d9386865311f1e3b03676cf02fd52bbc03b871c0762f704de2c79

Pith citing papers

Observation d4e76ec0-99d5-4883-bca9-5014f5d40301 · inbound

Normalizing Flows with Iterative Denoising cites this paper.

Normalizing Flows with Iterative Denoising Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:11:18.905947Z

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.

source=pdf_text observed=2026-05-10T02:11:31.246200Z digest=sha256:19556351f9f93756b10cdba7edad90a98817d97a131273059a5eefcabf4556db

Observation 0fc01b74-c007-4d87-9e0d-55c3c894b33e · inbound

From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models cites this paper.

From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-01T14:25:46.516825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:25:46.516825Z digest=sha256:5448c83d1b1fc21d4de22564db5556c7b8422cc0138b5f5f41da04c14d80709c