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Paper Citation Record · LEDGER

Analysis-ready Generative Unfolding

As of 16 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 2 inbound Pith citation observations for arXiv:2509.02708.

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

pith.paper-citation-record.v1
2509.02708 v1

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:41:37.018709Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:36:55.617103Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:25:47.359001Z

Reference resolution

66 of 66 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved63
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 422dfd15-cb87-4a5e-8894-27d0662130f3 · outbound

This paper cites The frontier of simulation-based inference.

Analysis-ready Generative Unfolding The frontier of simulation-based inference

Reference 1

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T16:41:36.701322Z digest=sha256:4233f4e323f816dc32653647b39c4352fbf4471ffefa18fd98adcb752f229352

Observation e8c2cd4d-bac7-48b0-8940-1450876c3755 · outbound

This paper cites Presenting Unbinned Differential Cross Section Results.

Analysis-ready Generative Unfolding Presenting Unbinned Differential Cross Section Results

Reference 2

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source=pdf_text observed=2026-08-15T16:41:36.707623Z digest=sha256:3e62fa8e4c429f8f09b9861abcea8357f3ab310866fb0d159d77adf582f381e8

Observation 10784fe9-56d6-43b0-8dc6-580de0ea9313 · outbound

This paper cites The Landscape of Unfolding with Machine Learning.

Analysis-ready Generative Unfolding The Landscape of Unfolding with Machine Learning

Reference 3

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source=pdf_text observed=2026-08-15T16:41:36.712623Z digest=sha256:b6a42e16ad41cc84abbb436d81e4c457beb380535b88d21ea18b4576343ea7fe

Observation c103547e-0be4-47e7-ac3d-2b416694488e · outbound

This paper cites Canelli et al.,A Practical Guide to Unbinned Unfolding, 2507.09582.

Analysis-ready Generative Unfolding Canelli et al.,A Practical Guide to Unbinned Unfolding, 2507.09582

Reference 4

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source=pdf_text observed=2026-08-15T16:41:36.717608Z digest=sha256:d979814464689a7da83092878e4969dcb0b6850bd64b4f40ce86ed75c3ce749d

Observation 6f3ee5ed-15da-4fd4-8090-3a8013deab43 · outbound

This paper cites OmniFold: A Method to Simultaneously Unfold All Observables.

Analysis-ready Generative Unfolding OmniFold: A Method to Simultaneously Unfold All Observables

Reference 5

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source=pdf_text observed=2026-08-15T16:41:36.722607Z digest=sha256:04e73acdf642eb56df2a451ab8ef1d32c12fb240ede35c91d3c0d70858acaf4a

Observation a89b6519-fb33-4386-b924-4e2e6ba4efec · outbound

This paper cites Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution.

Analysis-ready Generative Unfolding Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution

Reference 6

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no resolver link, observed 2026-08-15T16:41:36.728247Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.728247Z digest=sha256:04c9c58aaf6b016d00281bd43828fbe50ee458852fcbe157156e5d60994f576d

Observation 1dd4c517-39a7-4aa1-8a56-8874cd765efe · outbound

This paper cites A simultaneous unbinned differential cross section measurement of twenty-four $Z$+jets kinematic observables with the ATLAS detector.

Analysis-ready Generative Unfolding A simultaneous unbinned differential cross section measurement of twenty-four $Z$+jets kinematic observables with the ATLAS detector

Reference 7

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no resolver link, observed 2026-08-15T16:41:36.733508Z

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source=pdf_text observed=2026-08-15T16:41:36.733508Z digest=sha256:a659565504d387beec20ae813c9564c260071995b5e3ee6c09cabd83eaf7cc95

Observation a9879577-ad3d-4650-87e8-4cea8d1f9fae · outbound

This paper cites Measurement of jet track functions in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector.

Analysis-ready Generative Unfolding Measurement of jet track functions in $pp$ collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

Reference 8

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source=pdf_text observed=2026-08-15T16:41:36.738999Z digest=sha256:60c6b3c113d506264b5eceff0c95612d804dc25b5d312a36b52f706ab91540bc

Observation e6c614c4-490b-4b01-82ae-7650e2a20651 · outbound

This paper cites Disentangling Quarks and Gluons with CMS Open Data.

Analysis-ready Generative Unfolding Disentangling Quarks and Gluons with CMS Open Data

Reference 9

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source=pdf_text observed=2026-08-15T16:41:36.744180Z digest=sha256:1add1a0c3cea148111f3fe5c17a7f4751f2f60fdcdce6f896348d552b3ba93d9

Observation 861caae6-c1a3-4ad2-b2cb-c0dcaa979b14 · outbound

This paper cites an unresolved cited work.

Analysis-ready Generative Unfolding Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-15T16:41:36.751405Z digest=sha256:900dc2c41ef9a7b14a69d60ed62be6674c085e751418eba223ec0ab335f92ef8

Observation 67c971ab-adba-4ad4-9132-d293078845fb · outbound

This paper cites Multidifferential study of identified charged hadron distributions in $Z$-tagged jets in proton-proton collisions at $\sqrt{s}=$13 TeV.

Analysis-ready Generative Unfolding Multidifferential study of identified charged hadron distributions in $Z$-tagged jets in proton-proton collisions at $\sqrt{s}=$13 TeV

Reference 11

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source=pdf_text observed=2026-08-15T16:41:36.756384Z digest=sha256:ba8af5d078f06d21ba50ca20d7ca28ec653d300258e0538c6061803ce51bf90e

Observation bfd11698-e253-4a49-a024-d2b83fd04c0e · outbound

This paper cites an unresolved cited work.

Analysis-ready Generative Unfolding Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-15T16:41:36.761407Z digest=sha256:c888448017f4b7ef13f8b2e55249bf6c3b6fc1d6fa2a937cbf32a78349581751

Observation 804e9882-d61a-4f50-95f3-41e88a164e34 · outbound

This paper cites an unresolved cited work.

Analysis-ready Generative Unfolding Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-15T16:41:36.765959Z digest=sha256:bb3af953957a0f491581bebb705e927a91541f6059b78eb628f39c31f97a4b57

Observation a5b66b1c-bddf-4612-944b-529a7536cb37 · outbound

This paper cites an unresolved cited work.

Analysis-ready Generative Unfolding Unresolved cited work

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.771194Z digest=sha256:7ce5c2d75a47017ea503268100fb868be4d1106ae4513661e9a84c002eebd1f3

Observation bcb2927c-d313-4e58-9183-d1c671d80ae1 · outbound

This paper cites Towards Unfolding All Particles in HighQ2 DIS Events.

Analysis-ready Generative Unfolding Towards Unfolding All Particles in HighQ2 DIS Events

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T16:41:38.463994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 01f7be8d-ed1f-49b1-8370-59f2dca085f7 · outbound

This paper cites Measurement of CollinearDrop jet mass and its correlation with SoftDrop groomed jet substructure observables in $\sqrt{s}=200$ GeV $pp$ collisions by STAR.

Analysis-ready Generative Unfolding Measurement of CollinearDrop jet mass and its correlation with SoftDrop groomed jet substructure observables in $\sqrt{s}=200$ GeV $pp$ collisions by STAR

Reference 16

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source=pdf_text observed=2026-08-15T16:41:36.780307Z digest=sha256:d818451af74ffdb88cfa07fe3e0c9b4e28b2887be4ba983ea83f4bee0befe438

Observation c5daf417-2bc5-438b-946a-15924604d47d · outbound

This paper cites Generalized angularities measurements from STAR at $\sqrt{s_{\rm NN}} = $ 200 GeV.

Analysis-ready Generative Unfolding Generalized angularities measurements from STAR at $\sqrt{s_{\rm NN}} = $ 200 GeV

Reference 17

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source=pdf_text observed=2026-08-15T16:41:36.785589Z digest=sha256:5cc6357908bad94c0d5c087e6b40fba0dd28a01b55ff7f343e4e05c785c6c095

Observation cd6b6750-8824-4c80-9816-9a85b337a2be · outbound

This paper cites Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements with the OmniFold Technique.

Analysis-ready Generative Unfolding Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements with the OmniFold Technique

Reference 18

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no resolver link, observed 2026-08-15T16:41:36.790700Z

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source=pdf_text observed=2026-08-15T16:41:36.790700Z digest=sha256:2236c5cb30a6a5f5d7ddf3a714c1e48db3299c81bf8d2c3f72f08591443fe50d

Observation 44939c5c-1fea-4791-bae5-4e1f1e69ceed · outbound

This paper cites Analysis note: measurement of thrust in $e^{+}e^{-}$ collisions at $\sqrt{s}$ = 91 GeV with archived ALEPH data.

Analysis-ready Generative Unfolding Analysis note: measurement of thrust in $e^{+}e^{-}$ collisions at $\sqrt{s}$ = 91 GeV with archived ALEPH data

Reference 19

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no resolver link, observed 2026-08-15T16:41:36.795686Z

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source=pdf_text observed=2026-08-15T16:41:36.795686Z digest=sha256:8c8bb5e198d8fdaac06a25b2280605ad53dd8e0337538a329abbef576b8a5c4b

Observation 0c9a3d30-915d-4728-ade1-5cb7d2bece6a · outbound

This paper cites Unfolding with Generative Adversarial Networks.

Analysis-ready Generative Unfolding Unfolding with Generative Adversarial Networks

Reference 20

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source=pdf_text observed=2026-08-15T16:41:36.800627Z digest=sha256:78e9f11e7e3f61bb8d3f2c38ddc679c61e6c20a06e27cb41ef28aba638292316

Observation d71494b5-649c-4b35-ba26-f389d0233f26 · outbound

This paper cites How to GAN away Detector Effects.

Analysis-ready Generative Unfolding How to GAN away Detector Effects

Reference 21

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source=pdf_text observed=2026-08-15T16:41:36.805791Z digest=sha256:b590b7bd83806f58c75c5cc44d80456fa8f83b82b0f137de3dd8e22b65887501

Observation db061866-ce4f-4876-9b91-89948cbaf9e7 · outbound

This paper cites Invertible Networks or Partons to Detector and Back Again.

Analysis-ready Generative Unfolding Invertible Networks or Partons to Detector and Back Again

Reference 22

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Unavailable: canonical work link unavailable.

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Observation b31d9188-ebba-42db-8e22-66765992dbbe · outbound

This paper cites Learning to Simulate High Energy Particle Collisions from Unlabeled Data.

Analysis-ready Generative Unfolding Learning to Simulate High Energy Particle Collisions from Unlabeled Data

Reference 23

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source=pdf_text observed=2026-08-15T16:41:36.815637Z digest=sha256:90370f079dac00af9c3fc494307c519c4b9c269fa2cbe8ec15b4456298d0f2e8

Observation 1a078651-c5a1-4515-86f4-1af589e2fc5c · outbound

This paper cites An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training.

Analysis-ready Generative Unfolding An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 24

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source=pdf_text observed=2026-08-15T16:41:36.820513Z digest=sha256:140e49849d63913072e45fdf526d9b71dad12f6d688a69d671aa7ac7b216419c

Observation 0be1c044-e7fc-43b3-bd20-9a8876555c51 · outbound

This paper cites Returning CP-Observables to The Frames They Belong.

Analysis-ready Generative Unfolding Returning CP-Observables to The Frames They Belong

Reference 25

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source=pdf_text observed=2026-08-15T16:41:36.825617Z digest=sha256:9f44a65eb2c8a782b89d4173c06a2a8f9d71ad849cdbdc8c22930cea2d02baea

Observation 321693f9-9459-407a-8b93-aa1178fa7248 · outbound

This paper cites End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics.

Analysis-ready Generative Unfolding End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics

Reference 26

Resolution
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source=pdf_text observed=2026-08-15T16:41:36.830499Z digest=sha256:0a37eb1a0bc1d1d5b487aaebe17e62ef499220dfb29e2f48ea9b9a1003d46d1c

Observation d71a4094-24dc-498e-8021-16d3cdf55cf1 · outbound

This paper cites Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion.

Analysis-ready Generative Unfolding Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion

Reference 27

Resolution
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no resolver link, observed 2026-08-15T16:41:36.835314Z

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source=pdf_text observed=2026-08-15T16:41:36.835314Z digest=sha256:1e25290326ad2b0357d8b887c6827cdf1e7ad41e387372fccb07841170f4d978

Observation 7ca3746f-803a-4528-a682-384d1074fc43 · outbound

This paper cites Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models.

Analysis-ready Generative Unfolding Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models

Reference 28

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation afd27b27-ee21-42d2-8ce0-9c40811979e8 · outbound

This paper cites How to Unfold Top Decays.

Analysis-ready Generative Unfolding How to Unfold Top Decays

Reference 29

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Source-reported events for the cited work

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Observation ae6271bb-709f-45c1-aef8-114d45cefb3f · outbound

This paper cites Diefenbacher, G.-H.

Analysis-ready Generative Unfolding Diefenbacher, G.-H

Reference 30

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Observation 32d0d641-be6a-4149-96ff-2763c3127e93 · outbound

This paper cites Kicking it Off(-shell) with Direct Diffusion.

Analysis-ready Generative Unfolding Kicking it Off(-shell) with Direct Diffusion

Reference 31

Resolution
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Observation dad4d17f-1a2d-4c8f-816f-40ba694b467c · outbound

This paper cites Generative Unfolding with Distribution Mapping.

Analysis-ready Generative Unfolding Generative Unfolding with Distribution Mapping

Reference 32

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Observation d536fc29-f47f-4bf1-bbd0-e9adea3bc923 · outbound

This paper cites Machine learning-based event generator for electron-proton scattering.

Analysis-ready Generative Unfolding Machine learning-based event generator for electron-proton scattering

Reference 33

Resolution
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Source-reported events for the cited work

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Observation 8924c318-5566-4b7b-a887-b2e2077ef3f6 · outbound

This paper cites Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.

Analysis-ready Generative Unfolding Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference

Reference 34

Resolution
unresolved
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Observation 9730440b-2171-404c-8ed3-2aa1fc86250c · outbound

This paper cites Simulation-Prior Independent Neural Unfolding Procedure.

Analysis-ready Generative Unfolding Simulation-Prior Independent Neural Unfolding Procedure

Reference 35

Resolution
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no resolver link, observed 2026-08-15T16:41:36.873251Z

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Observation 2bec63cf-d4b4-4b8b-92aa-970626852d34 · outbound

This paper cites High-Dimensional Unfolding in Large Backgrounds.

Analysis-ready Generative Unfolding High-Dimensional Unfolding in Large Backgrounds

Reference 36

Resolution
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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.877768Z digest=sha256:4fdc810eda71ac827aa9334830fa64890a3ed87bc7ac47b78e4d61f1db6e1371

Observation 36276c7e-8c66-48b5-a0a2-738abedab909 · outbound

This paper cites Understanding Event-Generation Networks via Uncertainties.

Analysis-ready Generative Unfolding Understanding Event-Generation Networks via Uncertainties

Reference 37

Resolution
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Observation 8d473795-cf4d-40d7-af00-645089d10919 · outbound

This paper cites A Neural Resampler for Monte Carlo Reweighting with Preserved Uncertainties.

Analysis-ready Generative Unfolding A Neural Resampler for Monte Carlo Reweighting with Preserved Uncertainties

Reference 38

Resolution
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Source-reported events for the cited work

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Observation d2f6e197-c3d8-427d-ac6f-2d780d0274fc · outbound

This paper cites How to GAN Event Subtraction.

Analysis-ready Generative Unfolding How to GAN Event Subtraction

Reference 39

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no resolver link, observed 2026-08-15T16:41:36.891650Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.891650Z digest=sha256:573d3fff8baafa2732957da3cb0a2133e6b1fb26388e92ef3aae9069a0751686

Observation ac02e3e3-393b-4df1-8fc2-6611b2334784 · outbound

This paper cites Residual ANODE.

Analysis-ready Generative Unfolding Residual ANODE

Reference 40

Resolution
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no resolver link, observed 2026-08-15T16:41:36.896522Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.896522Z digest=sha256:3b1889161d22124b37c5bd12f310a8831dd44f22e60b63e4610067388ee4a18e

Observation f5b98bcd-cac4-44f7-832c-7a25c887beff · outbound

This paper cites Generator Based Inference (GBI).

Analysis-ready Generative Unfolding Generator Based Inference (GBI)

Reference 41

Resolution
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no resolver link, observed 2026-08-15T16:41:36.901291Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.901291Z digest=sha256:a1b2df6e41dabfa83444d271c52f04a0f6f352d6c1ab83ea6a540eb0ccb77bb1

Observation f4415e76-2cf7-44f9-a670-11fe51a036f0 · outbound

This paper cites Efficiency Parameterization with Neural Networks.

Analysis-ready Generative Unfolding Efficiency Parameterization with Neural Networks

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:41:37.521488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:41:36.906101Z digest=sha256:af4bbffffc9e26e63e7953199aa2e7ec63e626ffb6120a852e0c19cb9c1f5ceb

Observation 371226f8-f08f-4636-aeb0-4dd32b5615ef · outbound

This paper cites Precision-Machine Learning for the Matrix Element Method.

Analysis-ready Generative Unfolding Precision-Machine Learning for the Matrix Element Method

Reference 43

Resolution
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no resolver link, observed 2026-08-15T16:41:36.910653Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.910653Z digest=sha256:2791fe6922f87a56210e8323d01883ff2b70d9a7a86efcf6f873313c592bc370

Observation 72312384-1fec-466c-8e38-b43af03aef3b · outbound

This paper cites Flow Matching for Generative Modeling.

Analysis-ready Generative Unfolding Flow Matching for Generative Modeling

Reference 44

Resolution
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no resolver link, observed 2026-08-15T16:41:36.915309Z

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source=pdf_text observed=2026-08-15T16:41:36.915309Z digest=sha256:3b79d27021ffcea187f754b7111f59f5b7a9eb02599c86f2877aa8a0e7e51863

Observation 413c9619-efac-4e08-b1ae-0942c21a3385 · outbound

This paper cites Jet Diffusion versus JetGPT -- Modern Networks for the LHC.

Analysis-ready Generative Unfolding Jet Diffusion versus JetGPT -- Modern Networks for the LHC

Reference 45

Resolution
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no resolver link, observed 2026-08-15T16:41:36.919815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.919815Z digest=sha256:9e3b11204f274363debf284bbeb5f07843cf5b8c3f12ae3c9c8611a5f8925501

Observation 1e9b39cf-9541-4730-85ff-c2384fae77d6 · outbound

This paper cites EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion.

Analysis-ready Generative Unfolding EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion

Reference 46

Resolution
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no resolver link, observed 2026-08-15T16:41:36.924364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.924364Z digest=sha256:b6b97dff74d97bcc2c276f07fd3dd38f45203f132cdac21e65a7569af492fcc7

Observation 41b6169a-2542-48bf-af7b-42e5f07299ce · outbound

This paper cites Brehmer, V.

Analysis-ready Generative Unfolding Brehmer, V

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.929008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.929008Z digest=sha256:41ef89aa26ce22ace2867c7cdfd1facfdb85441da633dc17903ac33f7e7b83d5

Observation 1fd31c7a-4c9d-4f90-8e2c-05b651e7dc08 · outbound

This paper cites Parnassus: An Automated Approach to Accurate, Precise, and Fast Detector Simulation and Reconstruction.

Analysis-ready Generative Unfolding Parnassus: An Automated Approach to Accurate, Precise, and Fast Detector Simulation and Reconstruction

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.933308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.933308Z digest=sha256:b65b5c0735d684a7bf5c36fd62b986273368d0abeb6dd5a8205279cc45770bd6

Observation 9e1ba791-3a99-4e77-9501-c412330d7f91 · outbound

This paper cites CaloDREAM -- Detector Response Emulation via Attentive flow Matching.

Analysis-ready Generative Unfolding CaloDREAM -- Detector Response Emulation via Attentive flow Matching

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.938143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.938143Z digest=sha256:263fbddcf7374f9c5d0f0ebff9396d1ad6167876403329230ee0b75b5deecf01

Observation cd21bc67-3ec8-4ccd-8480-d3d6c1940eaa · outbound

This paper cites Efficient many-jet event generation with Flow Matching.

Analysis-ready Generative Unfolding Efficient many-jet event generation with Flow Matching

Reference 50

Resolution
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no resolver link, observed 2026-08-15T16:41:36.942683Z

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source=pdf_text observed=2026-08-15T16:41:36.942683Z digest=sha256:1ce7b31babb60783ef0e7658b15f46c7e3e762e4c9dbf92f989c9f7ba005aad8

Observation 5c9ff44f-a63a-4411-a5c1-567541e7477e · outbound

This paper cites An Introduction to PYTHIA 8.2.

Analysis-ready Generative Unfolding An Introduction to PYTHIA 8.2

Reference 51

Resolution
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no resolver link, observed 2026-08-15T16:41:36.947457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.947457Z digest=sha256:1934bad1390489335a8a58b64a6030710c9984fa29f2edc7999abc77d65794f0

Observation a28ce4dc-2f53-41f0-a9b4-a34eb87199ad · outbound

This paper cites Herwig++ Physics and Manual.

Analysis-ready Generative Unfolding Herwig++ Physics and Manual

Reference 52

Resolution
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no resolver link, observed 2026-08-15T16:41:36.952210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.952210Z digest=sha256:d8eb0ada5abe3273d80260d6b9b5b863369209e85af83df3c249fa2c0471d886

Observation 090b8537-9bf2-419f-9a5e-f0c2b7f1643b · outbound

This paper cites Reweighting Parton Showers.

Analysis-ready Generative Unfolding Reweighting Parton Showers

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.956866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.956866Z digest=sha256:0c5927fe925ce24381707a33130212fb860f5792a0d4d4223e3e68104ff5a94e

Observation 14657f9f-0702-46d8-9449-3fcb4c0d7800 · outbound

This paper cites Herwig 7.1 Release Note.

Analysis-ready Generative Unfolding Herwig 7.1 Release Note

Reference 54

Resolution
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no resolver link, observed 2026-08-15T16:41:36.961546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.961546Z digest=sha256:ab9ed0155e43b0e12391ba83c6ec9bc2288c9c66d8808bddd2c17c17e56fbd2f

Observation eeae09bc-df68-4030-b2ae-d3b9bf2ad4d5 · outbound

This paper cites DELPHES 3, A modular framework for fast simulation of a generic collider experiment.

Analysis-ready Generative Unfolding DELPHES 3, A modular framework for fast simulation of a generic collider experiment

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.966272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.966272Z digest=sha256:ba6aaa1a42b65de1ff0e23b7ddd98d10d08e87324580116e427e9b23a5264591

Observation 20ccdff7-db3c-4db2-be37-b1c0800bed9a · outbound

This paper cites FastJet user manual.

Analysis-ready Generative Unfolding FastJet user manual

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.971060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.971060Z digest=sha256:07e43801556d600569e7286c7135c64e3ca6557ca24313dd034bcffa3f857af4

Observation c48cb997-722b-45a6-8184-bb98cc0fb0e6 · outbound

This paper cites The anti-k_t jet clustering algorithm.

Analysis-ready Generative Unfolding The anti-k_t jet clustering algorithm

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.976061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.976061Z digest=sha256:f377990deaacac8fca36ead7fd69ff0d42e759b94ea3ece44d5140ef1ba308ba

Observation 9f97c791-b8b6-4eb0-8a4c-abde97384b3b · outbound

This paper cites Jet Trimming.

Analysis-ready Generative Unfolding Jet Trimming

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.980663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.980663Z digest=sha256:23846f64c0943c687c4276422aa6bd9ee6bed2bc93188dc93abcae2e6c64ee58

Observation 311d0a3b-f29a-41ed-bc02-f52e6a176dfc · outbound

This paper cites Recombination Algorithms and Jet Substructure: Pruning as a Tool for Heavy Particle Searches.

Analysis-ready Generative Unfolding Recombination Algorithms and Jet Substructure: Pruning as a Tool for Heavy Particle Searches

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.985299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.985299Z digest=sha256:6f390853fe105c5e7198c21fcff5c164946ed95a35504ecb0a5b82e9c0a32182

Observation 7eadc8c7-7b63-494d-89d6-36eda8871413 · outbound

This paper cites Techniques for improved heavy particle searches with jet substructure.

Analysis-ready Generative Unfolding Techniques for improved heavy particle searches with jet substructure

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.990244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.990244Z digest=sha256:ea4bf437ca26f135105836fcdd15aea9a86958eca0df63f3440601eb22462e2d

Observation 5dc7d7c5-712f-429a-aa9d-616b322e49d7 · outbound

This paper cites Towards an understanding of jet substructure.

Analysis-ready Generative Unfolding Towards an understanding of jet substructure

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:36.995453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:36.995453Z digest=sha256:6c047182965267dcd7821ca7b40fdef93954b6a8b66fa339bed8becd60e0e313

Observation 598b399c-949a-43cb-84f7-c2e193a1ae10 · outbound

This paper cites Soft Drop.

Analysis-ready Generative Unfolding Soft Drop

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:37.000220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:37.000220Z digest=sha256:4395ea8da4c900a7b6d2a0d4190767859be10e4d58c17dadc5418a3bfbe65bb2

Observation 1033600d-9105-4e90-90a4-5964fb85c7bb · outbound

This paper cites Identifying Boosted Objects with N-subjettiness.

Analysis-ready Generative Unfolding Identifying Boosted Objects with N-subjettiness

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:37.004918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:37.004918Z digest=sha256:25139073bc967e1d73246a705e3787495153ef69212f02d24faa7fcdcc242513

Observation 671ce155-0696-408a-8cc4-29f979a99bd0 · outbound

This paper cites Maximizing Boosted Top Identification by Minimizing N-subjettiness.

Analysis-ready Generative Unfolding Maximizing Boosted Top Identification by Minimizing N-subjettiness

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:37.009463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:37.009463Z digest=sha256:7480db36257b433d1022f7cf3db746af04f3453b136f8ce7df81089a23c40d17

Observation 47c3c0a8-8fab-4832-b048-855efcad7cbd · outbound

This paper cites Tools for Unbinned Unfolding.

Analysis-ready Generative Unfolding Tools for Unbinned Unfolding

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:37.014276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:37.014276Z digest=sha256:3870fbe28a4bfdf9ac686bf88f50cd87299a2012ef5e821f2a693f19b09a7e07

Observation eef04283-08a2-4911-8849-bd95a7b86379 · outbound

This paper cites Stay Positive: Neural Refinement of Sample Weights.

Analysis-ready Generative Unfolding Stay Positive: Neural Refinement of Sample Weights

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-15T16:41:37.018709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:41:37.018709Z digest=sha256:a118a1b83c3de858270a2aac0d4e03f379ff0a5f62c983605b85d761f17d6664

Pith citing papers

Observation fd4b3ef6-2f15-4029-a0f1-6959f89ce059 · inbound

Profiling systematic uncertainties in Simulation-Based Inference with Factorizable Normalizing Flows cites this paper.

Profiling systematic uncertainties in Simulation-Based Inference with Factorizable Normalizing Flows Analysis-ready Generative Unfolding

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-02T23:36:55.617103Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:36:55.617103Z digest=sha256:87fbbf61e11dca2ca0c9d6dd179bf4b2a72ef15dee7e7904ef35ff7f0c26921e

Observation bc47cbd2-ba80-476a-9462-52114e6367e5 · inbound

Factorizable Normalizing Flows for parameter-dependent density morphing cites this paper.

Factorizable Normalizing Flows for parameter-dependent density morphing Analysis-ready Generative Unfolding

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-01T15:25:47.360645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T03:41:22.092575Z digest=sha256:91ecd986516b74babc1f27764aff32d5bf417793734b729a88490e496b5587c8