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Paper Citation Record · LEDGER

Fast Score-Based Sampling via Log-Concave Reductions

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2512.24152.

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

pith.paper-citation-record.v1
2512.24152 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T13:36:16.126930Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0be1ba26-b6ff-4a6f-9c8c-be1b23ccffd3 · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Fast Score-Based Sampling via Log-Concave Reductions Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:13.354749Z digest=sha256:fd6086f70f6bf2fb44211ea79bf7c6249366d31baa192a499528561a6d85e8f0

Observation 5ac679d9-b798-4618-b7af-24080ac65c1e · outbound

This paper cites Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions.

Fast Score-Based Sampling via Log-Concave Reductions Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

Reference 3

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source=pdf_text observed=2026-08-03T13:36:13.734744Z digest=sha256:0c47645a59c83b5ddf118593dad27ed098d70e2295689061b29e6aba4071431c

Observation aa58cfdf-d999-487c-9cc8-a6a178219a7b · outbound

This paper cites KL Convergence Guarantees for Score diffusion models under minimal data assumptions.

Fast Score-Based Sampling via Log-Concave Reductions KL Convergence Guarantees for Score diffusion models under minimal data assumptions

Reference 7

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source=pdf_text observed=2026-08-03T13:36:14.425771Z digest=sha256:5f142160244eca2e51857c4689abfd2e86f5c1aa991cefac6188d7ff2d89e10f

Observation 03964175-1ba8-4dcb-80f3-e66077e73a53 · outbound

This paper cites Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data.

Fast Score-Based Sampling via Log-Concave Reductions Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:14.957638Z digest=sha256:9a437512be8d38df40b42844a861fec712f3a99222acff2c3017d34715b09294

Observation 2981070c-1bd3-408f-b740-73ce07777a08 · outbound

This paper cites Minimax Optimality of the Probability Flow ODE for Diffusion Models.

Fast Score-Based Sampling via Log-Concave Reductions Minimax Optimality of the Probability Flow ODE for Diffusion Models

Reference 11

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:15.126645Z digest=sha256:8d7b73da54734d5eadc50948e5d2489570e108f7a12b877bdda66fc1608de73b

Observation 44d51322-70f3-4c8b-addb-1d02cb84072b · outbound

This paper cites An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization.

Fast Score-Based Sampling via Log-Concave Reductions An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization

Reference 12

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source=pdf_text observed=2026-08-03T13:36:15.364750Z digest=sha256:9b511d63dcc33815f495a528ce03c1a326bc168083bcc56f60a63a0c85b18193

Observation 0f2bed86-b491-4d96-a098-7cf3e88167c5 · outbound

This paper cites Query lower bounds for log-concave sampling.

Fast Score-Based Sampling via Log-Concave Reductions Query lower bounds for log-concave sampling

Reference 13

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no resolver link, observed 2026-08-03T13:36:15.474745Z

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source=pdf_text observed=2026-08-03T13:36:15.474745Z digest=sha256:11b65c4a6bc129c0281d2b88c33e36c098619d15eb4389e6e96aaf0721eee8e6

Observation 192c4f91-df63-4185-85bc-b92d9702b9da · outbound

This paper cites Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models.

Fast Score-Based Sampling via Log-Concave Reductions Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models

Reference 16

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source=pdf_text observed=2026-08-03T13:36:15.764744Z digest=sha256:ff28d5f55b5ad685d2f589d6d236bee4076a90d4cbed946326ef8317b6addac9

Observation 5ab5795b-ca8f-4c7d-b51d-846d6ae57f51 · outbound

This paper cites A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry.

Fast Score-Based Sampling via Log-Concave Reductions A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry

Reference 17

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no resolver link, observed 2026-08-03T13:36:15.876867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:15.876867Z digest=sha256:b1af75a0c7e92c429034ae8b738aa6e3aa8b1a664125e8914ffd0d3780db0a6f

Observation 7d3aa0ed-2a30-4142-9f42-be1fe78e390b · outbound

This paper cites Benton, V.

Fast Score-Based Sampling via Log-Concave Reductions Benton, V

Reference 1982

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no resolver link, observed 2026-08-03T13:36:13.961658Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:13.961658Z digest=sha256:71d8734cf22722ffa3bc1d9b636b8f26bf0377933ceeb48890b03d58f05fdfb6

Observation 3298b6aa-ae42-40f7-a709-2a1dcb00bbaa · outbound

This paper cites Huang, Y.

Fast Score-Based Sampling via Log-Concave Reductions Huang, Y

Reference 1986

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no resolver link, observed 2026-08-03T13:36:15.664743Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:15.664743Z digest=sha256:da84cb21fdf85091447a97079b7dc2916d462870766b707cca33a9c6259a1a04

Observation 6d13157d-5106-4f4b-b98c-1a7282e25106 · outbound

This paper cites Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices.

Fast Score-Based Sampling via Log-Concave Reductions Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices

Reference 2011

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:36:16.014744Z digest=sha256:cddbaa1873206bd2299018f4755ea05d11c980ec2ffbd05d93ecb0930bb3c953

Observation f031b6d8-b75b-495c-b10d-e288edc2acf6 · outbound

This paper cites an unresolved cited work.

Fast Score-Based Sampling via Log-Concave Reductions Unresolved cited work

Reference 2016

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source=pdf_text observed=2026-08-03T13:36:15.574746Z digest=sha256:b8fd01087407e43c3d0df52f2f0e687f6fdd76f730894df053fd5fee284150aa

Observation 95c5cc39-89ce-43de-a73d-6e6544c29a14 · outbound

This paper cites The probability flow ODE is provably fast.

Fast Score-Based Sampling via Log-Concave Reductions The probability flow ODE is provably fast

Reference 2018

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source=pdf_text observed=2026-08-03T13:36:14.304744Z digest=sha256:3626c85d2b1e4aa008f19d423feac7eac449d43e652a663c908a74d0682b1804

Observation 970c2baa-9697-4eb7-bcd0-d25477c225ab · outbound

This paper cites Linear Convergence of Diffusion Models Under the Manifold Hypothesis.

Fast Score-Based Sampling via Log-Concave Reductions Linear Convergence of Diffusion Models Under the Manifold Hypothesis

Reference 2021

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source=pdf_text observed=2026-08-03T13:36:15.947608Z digest=sha256:68a1ea6ec89431130bbb231c7f579eb525f9ad7170f764cba431a1ebde6247e9

Observation 5038599c-4058-4f31-865d-8fb2a2f67ffe · outbound

This paper cites Faster high-accuracy log-concave sampling via algorithmic warm starts.

Fast Score-Based Sampling via Log-Concave Reductions Faster high-accuracy log-concave sampling via algorithmic warm starts

Reference 2023

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source=pdf_text observed=2026-08-03T13:36:13.565126Z digest=sha256:94986d3a588658f9c8660cc0d1960d7060c837e4cd0bbe8af1a0d34a7892f88c

Observation c05dc99e-1b7c-48d3-9991-3b084fbe7508 · outbound

This paper cites Error Bounds for Flow Matching Methods.

Fast Score-Based Sampling via Log-Concave Reductions Error Bounds for Flow Matching Methods

Reference 2024

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source=pdf_text observed=2026-08-03T13:36:14.124739Z digest=sha256:83597b69ae00f39f1325e991d097cc16955b4b1b5062ae9654b8af970e3baf9f

Observation f08175fa-36d2-4fa9-8a69-2c22e97e7d4d · outbound

This paper cites an unresolved cited work.

Fast Score-Based Sampling via Log-Concave Reductions Unresolved cited work

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.