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Paper Citation Record · LEDGER

Leveraging generative models to assist Monte Carlo sampling

As of 11 August 2026, this Paper Citation Record lists 100 of 201 outbound references and 0 inbound Pith citation observations for arXiv:2608.07648.

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

pith.paper-citation-record.v1
2608.07648 v1

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measured 100 of 201 reference resolution

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Reference resolution

100 of 201 outbound references displayed

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External citation measurements

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Outbound references

Observation 2494f53b-a29b-4938-a273-201c23c8ae53 · outbound

This paper cites Communications in Mathematical Sciences , volume =.

Leveraging generative models to assist Monte Carlo sampling Communications in Mathematical Sciences , volume =

Reference 1

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This paper cites Normalizing.

Leveraging generative models to assist Monte Carlo sampling Normalizing

Reference 2

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Leveraging generative models to assist Monte Carlo sampling and Brubaker, Marcus A

Reference 3

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This paper cites Density Estimation Using.

Leveraging generative models to assist Monte Carlo sampling Density Estimation Using

Reference 4

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 5

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This paper cites Communications on Pure and Applied Mathematics , volume =.

Leveraging generative models to assist Monte Carlo sampling Communications on Pure and Applied Mathematics , volume =

Reference 6

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This paper cites Equivariant.

Leveraging generative models to assist Monte Carlo sampling Equivariant

Reference 8

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 9

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This paper cites Advances in Neural Information Processing Systems , volume =.

Leveraging generative models to assist Monte Carlo sampling Advances in Neural Information Processing Systems , volume =

Reference 10

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This paper cites e3nn: Euclidean Neural Networks.

Leveraging generative models to assist Monte Carlo sampling e3nn: Euclidean Neural Networks

Reference 11

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Leveraging generative models to assist Monte Carlo sampling Proceedings of the 32nd

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Leveraging generative models to assist Monte Carlo sampling Denoising

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Leveraging generative models to assist Monte Carlo sampling Stochastic Processes and their Applications , volume =

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Leveraging generative models to assist Monte Carlo sampling Building

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Leveraging generative models to assist Monte Carlo sampling Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Leveraging generative models to assist Monte Carlo sampling Boltzmann Generators:

Reference 21

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Leveraging generative models to assist Monte Carlo sampling Asymptotically unbiased estimation of physical observables with neural samplers

Reference 23

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Leveraging generative models to assist Monte Carlo sampling and Anders, Christopher J

Reference 24

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Leveraging generative models to assist Monte Carlo sampling Physical Review E , volume =

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Leveraging generative models to assist Monte Carlo sampling Efficient Estimation of Free Energy Differences from

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Leveraging generative models to assist Monte Carlo sampling Normalizing

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Leveraging generative models to assist Monte Carlo sampling The Journal of Chemical Physics , volume =

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Leveraging generative models to assist Monte Carlo sampling Normalizing flows for atomic solids

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Leveraging generative models to assist Monte Carlo sampling Estimating

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Leveraging generative models to assist Monte Carlo sampling Scalable

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Leveraging generative models to assist Monte Carlo sampling doi:10.48550/arXiv.2512.23930 , archiveprefix =

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Leveraging generative models to assist Monte Carlo sampling Estimating

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Leveraging generative models to assist Monte Carlo sampling and Shirts, Michael R

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Leveraging generative models to assist Monte Carlo sampling Particle

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Leveraging generative models to assist Monte Carlo sampling Performance of Machine-Learning-Assisted

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Leveraging generative models to assist Monte Carlo sampling NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport

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Leveraging generative models to assist Monte Carlo sampling Transport

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Observation a8d03d84-57a5-4bcd-96f5-ea03266fd256 · outbound

This paper cites and Marzouk, Youssef M.

Leveraging generative models to assist Monte Carlo sampling and Marzouk, Youssef M

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Observation 71e14b85-f8a4-4724-a2be-2dbe2411db21 · outbound

This paper cites and Papaspiliopoulos, O.

Leveraging generative models to assist Monte Carlo sampling and Papaspiliopoulos, O

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Observation ba8b2d1a-0bd9-485f-a4fe-a056aac076b3 · outbound

This paper cites Efficient Modelling of Trivializing Maps for Lattice $\phi^4$ Theory Using Normalizing Flows: A First Look at Scalability.

Leveraging generative models to assist Monte Carlo sampling Efficient Modelling of Trivializing Maps for Lattice $\phi^4$ Theory Using Normalizing Flows: A First Look at Scalability

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This paper cites Statistics and Computing , volume =.

Leveraging generative models to assist Monte Carlo sampling Statistics and Computing , volume =

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Observation 61c00fe0-46d3-4d36-a82b-541285b1de04 · outbound

This paper cites and Wang, Jian-Sheng , year = 1986, month = nov, journal =.

Leveraging generative models to assist Monte Carlo sampling and Wang, Jian-Sheng , year = 1986, month = nov, journal =

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Observation fdfaa986-fda8-4340-850c-d0f540666dac · outbound

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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Observation 5d2992ac-3234-4746-9b64-3f1ccdce8b0b · outbound

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Leveraging generative models to assist Monte Carlo sampling Exchange

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Observation a2613bef-3b1e-4c62-b11c-cbf1ca4ea098 · outbound

This paper cites Sequential.

Leveraging generative models to assist Monte Carlo sampling Sequential

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Observation dfbad4bc-da48-47a8-9d0e-e1d4eb0ed2d8 · outbound

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Leveraging generative models to assist Monte Carlo sampling and Iba, Y

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This paper cites The European Physical Journal C , volume =.

Leveraging generative models to assist Monte Carlo sampling The European Physical Journal C , volume =

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Observation 500811cd-6646-4fdc-ae6c-77cc68971a0d · outbound

This paper cites Efficient Mapping of Phase Diagrams with Conditional.

Leveraging generative models to assist Monte Carlo sampling Efficient Mapping of Phase Diagrams with Conditional

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This paper cites Machine Learning: Science and Technology , volume =.

Leveraging generative models to assist Monte Carlo sampling Machine Learning: Science and Technology , volume =

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Observation 157509f6-e609-4215-835a-757b9b344f4e · outbound

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

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This paper cites and Bose, Joey and Lin, Chen and Klein, Leon and Bronstein, Michael M.

Leveraging generative models to assist Monte Carlo sampling and Bose, Joey and Lin, Chen and Klein, Leon and Bronstein, Michael M

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Observation c4a3118e-816e-42c0-8d21-7928f4830b86 · outbound

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Leveraging generative models to assist Monte Carlo sampling Stochastic

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Observation ab06bde5-837a-471d-9746-294445e74ecb · outbound

This paper cites Annealed.

Leveraging generative models to assist Monte Carlo sampling Annealed

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Observation 1538ed5a-bb17-4249-bc4f-1b21f1abe720 · outbound

This paper cites Continual.

Leveraging generative models to assist Monte Carlo sampling Continual

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This paper cites Journal of High Energy Physics , volume =.

Leveraging generative models to assist Monte Carlo sampling Journal of High Energy Physics , volume =

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Observation 1fbe2859-b7da-4a2f-a4bc-1920f2b9d03f · outbound

This paper cites , year = 1997, month = apr, journal =.

Leveraging generative models to assist Monte Carlo sampling , year = 1997, month = apr, journal =

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Observation f7cdf7f2-7dba-47a4-a32f-b7e5ec2340a4 · outbound

This paper cites , year = 1998, month = mar, journal =.

Leveraging generative models to assist Monte Carlo sampling , year = 1998, month = mar, journal =

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Observation fc647c9a-f779-47df-ad07-e1a06ac95692 · outbound

This paper cites and Crooks, Gavin E.

Leveraging generative models to assist Monte Carlo sampling and Crooks, Gavin E

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Leveraging generative models to assist Monte Carlo sampling Sampling the Lattice

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This paper cites Numerical Determination of the Width and Shape of the Effective String Using.

Leveraging generative models to assist Monte Carlo sampling Numerical Determination of the Width and Shape of the Effective String Using

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Observation a1b1fbf3-7f06-487d-93d9-e6a25f8912fa · outbound

This paper cites Accelerating astronomical and cosmological inference with Preconditioned Monte Carlo.

Leveraging generative models to assist Monte Carlo sampling Accelerating astronomical and cosmological inference with Preconditioned Monte Carlo

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Leveraging generative models to assist Monte Carlo sampling Accelerated

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Observation cfb7f63a-bae6-4848-8454-6368c67aeb91 · outbound

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Leveraging generative models to assist Monte Carlo sampling Skipping the

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Observation eb5ff01f-bb05-47c5-9ce5-2cd2ba480c71 · outbound

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Leveraging generative models to assist Monte Carlo sampling Sampling

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Leveraging generative models to assist Monte Carlo sampling Flow Perturbation to Accelerate

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Leveraging generative models to assist Monte Carlo sampling Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks

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Leveraging generative models to assist Monte Carlo sampling Enhanced

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Observation 39545cfa-f5dd-46ec-ad9e-0b0e3014be08 · outbound

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Leveraging generative models to assist Monte Carlo sampling Speed-up of

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Observation aca2f4d1-d238-4641-a36d-cf978d3f504b · outbound

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Leveraging generative models to assist Monte Carlo sampling Generalized

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Leveraging generative models to assist Monte Carlo sampling Statistics and Computing , volume =

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Observation f4b0c2e7-8f54-4e34-beac-cbdbbf798b09 · outbound

This paper cites Physical Review E , volume =.

Leveraging generative models to assist Monte Carlo sampling Physical Review E , volume =

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Observation 24b362e3-3030-424c-8564-759255df76b7 · outbound

This paper cites and Kucukelbir, Alp and McAuliffe, Jon D.

Leveraging generative models to assist Monte Carlo sampling and Kucukelbir, Alp and McAuliffe, Jon D

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Observation b41993d3-d9a9-424d-b27e-d72f5fd92691 · outbound

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Leveraging generative models to assist Monte Carlo sampling and Ghahramani, Zoubin and Jaakkola, Tommi S

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Observation e8447618-29d7-431a-b18d-caf5e9012de2 · outbound

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Leveraging generative models to assist Monte Carlo sampling Variational

Reference 78

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Observation 675a562b-9743-44bf-9e88-b00ebe5e510b · outbound

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Leveraging generative models to assist Monte Carlo sampling Solving Statistical Mechanics Using Variational Autoregressive Networks

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 80

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 81

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Leveraging generative models to assist Monte Carlo sampling Physical Review D , volume =

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Observation 5136d038-e7ba-4783-aabf-ceb7cba8cb1b · outbound

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Leveraging generative models to assist Monte Carlo sampling Forty-Second

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Leveraging generative models to assist Monte Carlo sampling Improving

Reference 84

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Leveraging generative models to assist Monte Carlo sampling Mitigating mode collapse in normalizing flows by annealing with an adaptive schedule: Application to parameter estimation

Reference 85

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 86

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This paper cites Nature Machine Intelligence , volume =.

Leveraging generative models to assist Monte Carlo sampling Nature Machine Intelligence , volume =

Reference 87

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Leveraging generative models to assist Monte Carlo sampling Machine Learning: Science and Technology , volume =

Reference 88

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Leveraging generative models to assist Monte Carlo sampling Markovian

Reference 89

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Leveraging generative models to assist Monte Carlo sampling and Lederman, Roy R

Reference 90

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Leveraging generative models to assist Monte Carlo sampling Flow-based sampling for multimodal and extended-mode distributions in lattice field theory

Reference 91

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Leveraging generative models to assist Monte Carlo sampling Boosting Monte Carlo simulations of spin glasses using autoregressive neural networks

Reference 92

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Leveraging generative models to assist Monte Carlo sampling Machine-Learning-Assisted

Reference 93

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Leveraging generative models to assist Monte Carlo sampling Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization

Reference 94

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 95

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Leveraging generative models to assist Monte Carlo sampling Forty-First

Reference 96

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 97

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Leveraging generative models to assist Monte Carlo sampling Relaxing

Reference 98

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Leveraging generative models to assist Monte Carlo sampling Theoretical Guarantees for Sampling and Inference in Generative Models with Latent Diffusions , booktitle =

Reference 99

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Leveraging generative models to assist Monte Carlo sampling Unresolved cited work

Reference 100

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