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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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:ae2e5fa15d0d6d4554cd7f084bec845b91512bab47aae96e56a5fe0e84ea48f2

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=sha256:6c4c5082169c9e0f5a774f768816bb6d5aae7c594e82501189d4d9e511f4cd54

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=sha256:880997a5b9a9f0b2554b8b3e1c9bf419a8f3cc82963ed55684e3f1644d2da3cc

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=sha256:988a19fa817ef702519254ffad9f650d7b01a3fa2203d51f697ebbc7915bc37d

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:bfcab6e587fd696e11d23cd3c9bcedc14e8ea3d0357bcb5cf17dab4dd8eb47fa

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=sha256:75683b744db84de0ebba46befb7383a41b3c1596e25988a843e0c0b8dc9fb20c

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=sha256:9edcab9ae7eb23b236b8c16d3c2f4238092a9473fce86573f4015fa08b7c93f9

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:abebd5324785de9ff5795d803a1ea25cd6987d01edbcff3913846de66a1da3a5

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=sha256:0d4e415a6a36db94203c8b47fe8a17d995fe6246d0ed151a34a535c579b6df2c

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=sha256:39abd81b0ed13c19b435e0be4d2d883bbea5c030c794027e02967d5771617d11

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=sha256:25c52ffa7c7a1d82de40a29cef153dd495dfeb01a827e45771432b9de67066a3

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=sha256:3a8ef98377d34b85bbb6614977f001e2b62e330ed45043618552c41182128c9e

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=sha256:6651579963e3543384b419014319f0b247e3a7d58d444544d0105617d95c49b5

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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source=pdf_text observed=2026-08-06T21:24:20.245501Z digest=sha256:6eb127c47b724e9a07ddd5226abd853658af0947be5b502db8e6e4aa866a5c1c

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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source=pdf_text observed=2026-08-06T21:24:20.410336Z digest=sha256:12dde5c8638ff2e421c51a97fe8e77f6cde954556ca885f959714d8a891e343b

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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source=pdf_text observed=2026-08-06T21:24:20.522781Z digest=sha256:9ffc498266e49079ed6c086d93159279c9b80ab21231b829ddbd8457dec36759

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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source=pdf_text observed=2026-08-06T21:24:20.664903Z digest=sha256:3a50d1bd1480b50fac9133dfe972275b5e10da7d7a0a0d01a8c19d4921f17148

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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source=pdf_text observed=2026-08-06T21:24:20.796592Z digest=sha256:fa28746f5ac3b256a9f4812df1b51d5aebd396f801efea5320479ff4b01d9121

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:d329d4a5b387bf28b493a66afb096a7581598dccf4bc61395f610d74b5a59150

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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source=pdf_text observed=2026-08-06T21:24:21.092430Z digest=sha256:4b2e22eba40985e662b3d94393370c934f8240df01fef203576c71c741ccd563

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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source=pdf_text observed=2026-08-06T21:24:21.455218Z digest=sha256:ddd0e2cb36531692940a2b90ec5df93b646c635745401d022793d0a61a1129f8

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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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=sha256:28a4f02f0c62c40cdef37f6cacb1db8d82079cdaae87dc0978f7d9127f47965e

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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source=pdf_text observed=2026-08-06T21:24:21.933613Z digest=sha256:b506b5089a3e46b27e5436f0e1b7231cf1c52088a0b59b4586b748b1abcc4348

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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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:22.201556Z digest=sha256:83d9f4fb5845bb69dd6332176a14f68b87fe6ac6f798422dea996df9c5ac947c

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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source=pdf_text observed=2026-08-06T21:24:22.322355Z digest=sha256:35544ee6304e2cbeb7d8c3ee9cd9b12c856835b355d4d05c2a99e7a9f84be0f4

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

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:22.463397Z digest=sha256:af7abb1110deb2888b577d6a421a362deac499eace70d5f59f15cb2bfdfb9107

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:22.572157Z digest=sha256:7e5dae272fc36c48f7c790e655ec1b81441c02ac765f53858d3d7e98080841f1

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 2026-08-14T06:32:32.682623+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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:22.795297Z digest=sha256:7409d681b04b954ebea979b552e1ef44fa8b743848f7e363399ce9362cdc1d3a

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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source=pdf_text observed=2026-08-06T21:24:22.909852Z digest=sha256:a1d0bd48c2fc005bd42499d9e01d777c93526d16d07db731db3e4aa3311df8bf

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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source=pdf_text observed=2026-08-06T21:24:23.034557Z digest=sha256:31b657a8c64dcddae89caaf8c260b407bf98c6247d019487d4e861655e92e38d

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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source=pdf_text observed=2026-08-06T21:24:23.158094Z digest=sha256:f18c68d76fa84baf9d911971dba7f7db0f672570ef1a6ec73d49712ce9929222

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:23.302087Z digest=sha256:da73a025da010caebc4e0e01769507883de2eca9a7bbc66ef056b82c057353a9

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:23.443811Z digest=sha256:ca733fbc408aed00b2140d9a49c89ca991ee02f4cbdd5ed50f1b106595694a35

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:af3e81919aeb551da1e08f63ba4997184aaa31cfd031530e474ca3b2f7f6847e

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

Reference 39

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source=pdf_text observed=2026-08-06T21:24:23.695854Z digest=sha256:ddc05531773aa626bfe8b7821d93083fce605c5afc7dad96b1e96e22657ab0df

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:23.819363Z digest=sha256:e6b7a392c79117660309479429a50b58c303abf680a2654cc309e5cb280e023f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:23.963905Z digest=sha256:61da16a683e95e4bd5bec2747beac82b051b135f63bc968a22ca41a8b56c9dc7

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:24.076955Z digest=sha256:e509950bd36f67e84967853f6b779be5d3e59be4a01e48795c3e3f5c9dbf2e83

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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verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:24.163984Z digest=sha256:719b3043eaacd62501feaeb4a75e586e2e540d2c8c9e9935a9c9ef598853909b

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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no resolver link, observed 2026-08-06T21:24:24.305000Z

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source=pdf_text observed=2026-08-06T21:24:24.305000Z digest=sha256:736ab57d77c35ef27434ceb8207e3a901dc70483e99ce7dc620d1f907bda57b7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:24.442164Z digest=sha256:2a9d077097ba3f7e83c250727b5b306177f282a9f5dc025c2605f91b5439086f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:24.592456Z digest=sha256:a9d6b6161b660a92f1aaed0500855fd492b35a391d03d7b25cf84217dabe8e6d

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:24.731868Z digest=sha256:e160b5b9279b6688188b2cca71c42ed86aacf15eabbdc95bb6c9d57fdac46f0a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:24.899102Z digest=sha256:0d510fe0abb8a5bc5d8795fda86f975f4fbfd3c218ef498bd5a8d4c120645771

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-reported events for the cited work

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source=pdf_text observed=2026-08-06T21:24:25.021132Z digest=sha256:19d972c6a7f7a81add536032f64421d4abfd6eb698991ee70a39c01ae43ae6bb

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:25.126688Z digest=sha256:6cc1917ec13ed07326aca5b282b071b42f62963f6922470ee00eb79446498f03

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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verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:25.278502Z digest=sha256:2f469bcf7d9e4b354abd1532e96e80a2055845b855aa1429a6991506449e2a41

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:25.397582Z digest=sha256:734ee6cc3a3a6349c13ece663308cb8221b2d4f8c38a26e7505b709f0077c2fd

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:24:25.524981Z digest=sha256:4c712f6b0ae07484829433355b0efa293f4a0703765d323ec184bb3a1b3588a9

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=sha256:9ab2c5173edcebfbaef29a9333a7aaafacf6453f6b3668428925a6b2c55b5893

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:25.776995Z digest=sha256:6c27c7f6155d0d0b37931bc3855e221a4a91837e7039f33259e11cad9074ed53

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=sha256:9f6966d498395d564a798f970dbc535f113355a89eb554a52521ce6d8e2e879b

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
verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.132697Z digest=sha256:e5a20efae4a6e670c2a859c972cd3c35b1934f1f6b16f1ebb8054ef27e592874

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=sha256:59b07bacc418e6e67dae5c5f2e76a2f18a04c572f09173f76a1738b6cdac23f2

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.444783Z digest=sha256:fb2a7ad7997967aff68f742d1e15b7b45b9fc569a703898fb1dc84d9613d6aba

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.554940Z digest=sha256:fdefe94936eccf5674ff03676aa783606462763e3ff77d97f84d7c3f47f23a34

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.653129Z digest=sha256:7f7cd49b8c94af48f708c94692758be1a2dfaaf436ab1ca2528c9699f3591392

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.751868Z digest=sha256:184cff3d5cc7114418d246fc1cbb28db2240849041331bed3bbb0fb1e29c921e

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:bdf2b7b5d9110a0364812377f6ff7fc7e56e67657193f602e454ee3477a5f6d7

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.980251Z digest=sha256:8df7aaaae154db1bd76b9f5ca4147a246592f5e8ae3fb0da53cf5df50b0e556a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:27.129634Z digest=sha256:3f95fad6a2cd7a4eb98a9e15800036776ef242054e950afdc798eee86849c5cc

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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verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:27.255123Z digest=sha256:8e8d28115cb5a3d1c6d9481df4e270305255fda9b5326edf62ef708a17de106b

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:27.408607Z digest=sha256:126a7cb42dcb8851f2fc408240cc6577aa11550701915057fa0a12b2728b9978

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=sha256:0aee14534259455358b000e63ba40a581838d3847290d645608caf4fd1647a3c

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

Resolution
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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:b32bac00265e0231e3ae115a164fe6754a99e7de6a5f9ebfeabc70f11117547b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:27.750307Z digest=sha256:f2a81cdddaacd263d0e1238952ef41e5f805e26d8e5c27729bbe7545b908bd46

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

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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:e9b0aa61996b1c09713baae925c9706741700031e01ffd7129782174d70466e8

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.049428Z digest=sha256:176d35bd544345f962fb713807555152f1631b6f425d571e385a0625c20c5258

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.174819Z digest=sha256:af7238440a7dde62620015df4ff872abaad152498e3e0b770ea1698a0d1a55f7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.377318Z digest=sha256:53b292f172553a805cb14fc5be2deac6155489c85d56371610e129f9a70ec44b

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

Resolution
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:bb0e58492c34bc8644de30769895f42c7cf44a582c0653b0c857583c0754cab7

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.272137Z digest=sha256:1b272c8d8c426c9506cf6687629e8ad1683b6702285fac3fab08b757029169bd

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=sha256:73a5f36ade2465da95ea6a6a13302fd28a55cbf8949b4dddea0fddc4a76efe78

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.784523Z digest=sha256:d7fc536e1b71d04c88b517389a98a945e89751ad48377eb110be7723f55b5bcf

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.561659Z digest=sha256:b6a0293fe5fb3306d6035723211f6f53dcbf4fb76a265e9a172f8e09bfc8c010

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.181054Z digest=sha256:6380b508b126861eea3de87647ec66e0ac4cd8b74b30c0ca93a113c27e370fb9

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.998577Z digest=sha256:6e050cb9cfe0a8c05c651db319373762fb86d1f8424397c0ef97fe5ef072ef36

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.274671Z digest=sha256:9cc6030af3093a12b1b3a17d2ef3fa0295fdc0ea8ffacb6a924d0ebedff8557d

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.383326Z digest=sha256:9d171803c3a5fb3cbd7dcbdd22e723a90622a955e500a994bb0bb5c5693e9aa0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.497339Z digest=sha256:a06fbb7c0478a546dfaa7aa1d4116d5edbc8fb06ae7e076cf14f3fba799405b5

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.633740Z digest=sha256:dbceb20145cbb41a96aea8ead256c49c11a125cf99bfa352d9e884ff86eaef4b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.754262Z digest=sha256:95e36d5a59cdac7892381679ced407f6ee9909583e9e4e8cbd01f0588c039fa8

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.904072Z digest=sha256:6399410256cb88d49e7879aebe21996bfb139d777d293227f37bb05ca78f48c2

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:30.126211Z digest=sha256:8e33d46f57205d38a8840eea4d3461089855485c06192aee3fc8e0723beddfa4

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:30.338090Z digest=sha256:a783b885b484e569287b1291bbe04178fac4df06cafefd316de141bb1d530d56

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

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:24:32.389680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:30.496303Z digest=sha256:834044d5f161ab165c67a14ea6c3b2ad9b69daa1bbe493d05bc7491df5756d8c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:30.700258Z digest=sha256:e0ef7101479bcc5350199a02a03bc81c21d5229d4968da82d43f4d571caeb24e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:30.852858Z digest=sha256:53cea5c8e14aedad1e2e9cbb7e44177d979e7f2ba374ab36316208e98330dcdd

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:31.036828Z digest=sha256:1a228dc4c77c1302624a1d8cfee81fb81771a0da0185cb15724cafd3a7d93099

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:31.083975Z digest=sha256:0a268087c740244b6aa72deb4b123e41a3dec2d36bf1a7e298429858e155de90

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:31.103641Z digest=sha256:0d3ca48545b1f5400b083ed9ff6a861f749a8fe7351fef462f0abadc0ec2e3ef

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

Resolution
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:d9dca394fe453074e5343a349a255bffd7db4410d48563727223d7402891b132

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:29.094673Z digest=sha256:9e77a2788458e3669d2608f55476e61c99c8c57107a12a16ba75bf1d5fbd9d25

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:26.242084Z digest=sha256:2e739ff3ccb0f0c4865a666e5338d886f07b0cd56aa6ca1031dda1b7217c2c0e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-06T21:24:28.895823Z digest=sha256:a8ff68891189c620c905b1a47220803a2762a773103ee9b868cd92500bab072f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T02:11:31.246200Z digest=sha256:232c9a169959cd98144915cc84d1012b2f24e69a9bc5016c02f0f9c8d084b9e7

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=sha256:65d20572f403a999c741735a878e8a9234eefe3d827e3eb1ebf04e3dc2702aca