Paper Citation Record · LEDGER

On the query complexity of sampling from non-log-concave distributions

As of 12 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 2 inbound Pith citation observations for arXiv:2502.06200.

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

pith.paper-citation-record.v1
2502.06200 v3

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:31:00.171252Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T12:30:53.400656Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:16:03.235051Z

Reference resolution

38 of 38 outbound references displayed

verified exact1
verified fuzzy33
unresolved4
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c001a58-0b54-4949-ae5b-f4e70e279f7f · outbound

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

On the query complexity of sampling from non-log-concave distributions Faster high-accuracy log-concave sampling via algorithmic warm starts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.651959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2961944f-352b-49b0-b8e1-8cae0d43b1f9 · outbound

This paper cites An introduction to MCMC for machine learning.

On the query complexity of sampling from non-log-concave distributions An introduction to MCMC for machine learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.641681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9ba5e1d3-9b28-4682-b927-ca38e1dda26f · outbound

This paper cites Nearly d-linear convergence bounds for diffusion models via stochastic localization.

On the query complexity of sampling from non-log-concave distributions Nearly d-linear convergence bounds for diffusion models via stochastic localization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.630264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ed16ab5d-3924-4537-b575-99cf4efc430c · outbound

This paper cites Towards a theory of non-log-concave sampling:first-order stationarity guarantees for Langevin Monte Carlo.

On the query complexity of sampling from non-log-concave distributions Towards a theory of non-log-concave sampling:first-order stationarity guarantees for Langevin Monte Carlo

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.615326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 25b36be9-fe92-491d-80eb-d2dee3ac9f9e · outbound

This paper cites On extensions of the Brunn-Minkowski and Prékopa-Leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation.

On the query complexity of sampling from non-log-concave distributions On extensions of the Brunn-Minkowski and Prékopa-Leindler theorems, including inequalities for log concave functions, and with an application to the diffusion equation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.604702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0347a2ad-9cb3-415f-bb13-5dd88bdffc42 · outbound

This paper cites Convergence of Langevin MCMC in KL-divergence.

On the query complexity of sampling from non-log-concave distributions Convergence of Langevin MCMC in KL-divergence

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.594171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e5e9efd9-60e1-4738-bf26-9eb6dd4d55e0 · outbound

This paper cites Chatterji, Peter L.

On the query complexity of sampling from non-log-concave distributions Chatterji, Peter L

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.583131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0e80bf46-c2dd-4340-b358-215660e20763 · outbound

This paper cites The probability flow ODE is provably fast.

On the query complexity of sampling from non-log-concave distributions The probability flow ODE is provably fast

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.571601Z

Source-reported events for the cited work

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Observation e8113617-f6a6-4d66-ad21-a2b347f447ba · outbound

This paper cites Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.

On the query complexity of sampling from non-log-concave distributions Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.560807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9be334e9-9092-4ac2-bb78-d441b310713e · outbound

This paper cites Analysis of Langevin Monte Carlo from Poincar \'e to log-Sobolev.

On the query complexity of sampling from non-log-concave distributions Analysis of Langevin Monte Carlo from Poincar \'e to log-Sobolev

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.548213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ca829c05-ef81-47d2-a01d-98b5b8a5d1a2 · outbound

This paper cites On theoretical guarantees and a blessing of dimensionality for nonconvex sampling.

On the query complexity of sampling from non-log-concave distributions On theoretical guarantees and a blessing of dimensionality for nonconvex sampling

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ac6fae17-459e-4326-a0cf-00ed2403e25e · outbound

This paper cites Log-concave Sampling.

On the query complexity of sampling from non-log-concave distributions Log-concave Sampling

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.537805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c9efbd34-4fed-4710-8fb2-9bb9878a7fe6 · outbound

This paper cites Optimal dimension dependence of the Metropolis-adjusted Langevin algorithm.

On the query complexity of sampling from non-log-concave distributions Optimal dimension dependence of the Metropolis-adjusted Langevin algorithm

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.526595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b59898e2-6ccf-45d1-8e26-6a1cb77b72ea · outbound

This paper cites Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions.

On the query complexity of sampling from non-log-concave distributions Improved analysis of score-based generative modeling: User-friendly bounds under minimal smoothness assumptions

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.513234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 765a7124-0858-4cbe-9ac6-db03debec5d7 · outbound

This paper cites Simulation and Monte Carlo : With applications in finance and MCMC.

On the query complexity of sampling from non-log-concave distributions Simulation and Monte Carlo : With applications in finance and MCMC

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.498161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0cb617ca-fe7a-40a4-adfe-f8859cd0c543 · outbound

This paper cites Log-concave sampling: Metropolis-Hastings algorithms are fast.

On the query complexity of sampling from non-log-concave distributions Log-concave sampling: Metropolis-Hastings algorithms are fast

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.487592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ecc2382f-1edb-4d78-bcc2-9251c8053e9e · outbound

This paper cites On sampling from Ising models with spectral constraints.

On the query complexity of sampling from non-log-concave distributions On sampling from Ising models with spectral constraints

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.477081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d480154c-89af-4370-ba85-5a13d4b2edea · outbound

This paper cites Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling.

On the query complexity of sampling from non-log-concave distributions Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling

Reference 18

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Source-reported events for the cited work

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Observation 2ec0331f-ff3c-43dd-8846-c6ae4e9e11d2 · outbound

This paper cites Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation.

On the query complexity of sampling from non-log-concave distributions Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T16:31:00.085779Z

Source-reported events for the cited work

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Observation 3fd34f8c-e0f6-4f47-970d-a39e7a5c30b3 · outbound

This paper cites A separation in heavy-tailed sampling: Gaussian vs.

On the query complexity of sampling from non-log-concave distributions A separation in heavy-tailed sampling: Gaussian vs

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.468331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 76adaa45-f03a-49af-b956-9f88c7b8dc24 · outbound

This paper cites Weak Poincar\'e Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses.

On the query complexity of sampling from non-log-concave distributions Weak Poincar\'e Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T16:31:00.094068Z

Source-reported events for the cited work

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Observation d1bcc525-2f9b-48ae-9d5e-e5762aae540a · outbound

This paper cites Zeroth-order sampling methods for non-log-concave distributions: Alleviating metastability by denoising diffusion.

On the query complexity of sampling from non-log-concave distributions Zeroth-order sampling methods for non-log-concave distributions: Alleviating metastability by denoising diffusion

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.458225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a8cfb972-2cbf-490e-86e6-c8b534eb8373 · outbound

This paper cites Faster sampling without isoperimetry via diffusion-based Monte Carlo.

On the query complexity of sampling from non-log-concave distributions Faster sampling without isoperimetry via diffusion-based Monte Carlo

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.448910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9085ed3-6883-4ef3-a299-2f81f350f17b · outbound

This paper cites Sampling approximately low-rank Ising models: MCMC meets variational methods.

On the query complexity of sampling from non-log-concave distributions Sampling approximately low-rank Ising models: MCMC meets variational methods

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.439362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5cb68c46-51dd-48b9-b0eb-7f9c3fac4329 · outbound

This paper cites Statistical mechanics: algorithms and computations , volume 13.

On the query complexity of sampling from non-log-concave distributions Statistical mechanics: algorithms and computations , volume 13

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.429266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1526721d-2721-4b5c-8f37-cbce81c96429 · outbound

This paper cites A guide to Monte Carlo simulations in statistical physics.

On the query complexity of sampling from non-log-concave distributions A guide to Monte Carlo simulations in statistical physics

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.417438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7c6b3965-b468-46e8-b617-3507cca333f6 · outbound

This paper cites Concise formulas for the area and volume of a hyperspherical cap.

On the query complexity of sampling from non-log-concave distributions Concise formulas for the area and volume of a hyperspherical cap

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.406006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eb7f09c2-6421-44fe-b4ba-4d832ed100ce · outbound

This paper cites Convergence of score-based generative modeling for general data distributions.

On the query complexity of sampling from non-log-concave distributions Convergence of score-based generative modeling for general data distributions

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.395305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cd03e1b3-1d19-4edc-922b-69107111e2f2 · outbound

This paper cites Universal approximation using well-conditioned normalizing flows.

On the query complexity of sampling from non-log-concave distributions Universal approximation using well-conditioned normalizing flows

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.384081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ca7f4fa0-d7ce-44dd-a6f7-9d72995da74c · outbound

This paper cites Contraction and convergence rates for discretized kinetic Langevin dynamics.

On the query complexity of sampling from non-log-concave distributions Contraction and convergence rates for discretized kinetic Langevin dynamics

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.371973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cb97a0a0-673f-4cf8-9e9d-6b7aa4b5510a · outbound

This paper cites Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering Langevin Monte Carlo.

On the query complexity of sampling from non-log-concave distributions Beyond log-concavity: Provable guarantees for sampling multi-modal distributions using simulated tempering Langevin Monte Carlo

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.361152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 961fbe79-ea14-4fd8-ba4c-cdbf87c948b8 · outbound

This paper cites Sampling can be faster than optimization.

On the query complexity of sampling from non-log-concave distributions Sampling can be faster than optimization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.351192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 24cffbfe-fa0e-441f-a00c-13bbe7276015 · outbound

This paper cites Towards a complete analysis of Langevin Monte Carlo : Beyond Poincar \'e inequality.

On the query complexity of sampling from non-log-concave distributions Towards a complete analysis of Langevin Monte Carlo : Beyond Poincar \'e inequality

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.336557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0dd09a11-69fe-470e-96bc-c7b1b5633f96 · outbound

This paper cites Exponential convergence of Langevin distributions and their discrete approximations.

On the query complexity of sampling from non-log-concave distributions Exponential convergence of Langevin distributions and their discrete approximations

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.324654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b5a4a62-4659-423a-97fb-b97732b33ae1 · outbound

This paper cites The randomized midpoint method for log-concave sampling.

On the query complexity of sampling from non-log-concave distributions The randomized midpoint method for log-concave sampling

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.312555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8d82ce4c-c6c2-4b8c-be2e-250a39b001a7 · outbound

This paper cites Rapid convergence of the unadjusted Langevin algorithm: Isoperimetry suffices.

On the query complexity of sampling from non-log-concave distributions Rapid convergence of the unadjusted Langevin algorithm: Isoperimetry suffices

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.300574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 132f6fe9-86e2-488a-97b9-cb07c7e62d77 · outbound

This paper cites Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry.

On the query complexity of sampling from non-log-concave distributions Proximal Langevin Algorithm: Rapid Convergence Under Isoperimetry

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T16:31:00.166278Z

Source-reported events for the cited work

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Observation 276fad87-7d66-47c2-a7ef-2174e5252bcd · outbound

This paper cites Improved discretization analysis for underdamped Langevin Monte Carlo.

On the query complexity of sampling from non-log-concave distributions Improved discretization analysis for underdamped Langevin Monte Carlo

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T16:31:00.289359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation ebb8ed3b-a941-4fc0-8283-d8c74157268e · inbound

Query Lower Bounds for Diffusion Sampling cites this paper.

Query Lower Bounds for Diffusion Sampling On the query complexity of sampling from non-log-concave distributions

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:16:03.245743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a800f7a2-45d5-4a63-a277-c0cd9828c65e · inbound

The Universal Warmup Path: Automatic Preconditioner Selection for HMC cites this paper.

The Universal Warmup Path: Automatic Preconditioner Selection for HMC On the query complexity of sampling from non-log-concave distributions

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-30T12:30:53.400656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.