Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:47:22.890118Z
Paper Citation Record · LEDGER
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
As of 18 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2505.18300.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T23:22:35.875578Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T23:22:46.537900Z
Reference resolution
30 of 30 outbound references displayed
- verified exact2
- verified fuzzy16
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3a02bcfb-5d58-460a-888a-9789e5bd213f · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:27.539538Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4e973093-2c38-4878-967a-847a79476289 · outbound
This paper cites Name # of nodes.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Name # of nodes
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:26.417360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 73f74b98-7e10-4b49-b5db-c1a30a508db0 · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:26.170877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 716d0e08-d3a9-4255-bca8-3aed17a2502f · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:25.742406Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 32888924-1096-4106-96d3-186033192c63 · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:28.636789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation dbf362bf-c10b-4b76-8eeb-6ae57319f327 · outbound
This paper cites Improving Asymptotic Variance of MCMC Estimators: Non-reversible Chains are Better.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Improving Asymptotic Variance of MCMC Estimators: Non-reversible Chains are Better
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:47:20.667794Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3a3e5d8-6553-423e-a792-a5bab5a4ada8 · outbound
This paper cites N., and Zhang, R.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs N., and Zhang, R
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:28.425645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fb284262-244a-49a1-b11f-07a67d2b8a7b · outbound
This paper cites Challenging the limits: Sampling online social networks with cost constraints.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Challenging the limits: Sampling online social networks with cost constraints
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:27.913858Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 40c7843a-f2eb-458c-aea8-0dd247d20fe1 · outbound
This paper cites Proof of Lemma 3.2 The proof consists of three parts: We first show that V (x) = X i∈X µi(xi/µi)−α (26) is the Lyapunov function of the ODE ˙x = π[x] − x.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Proof of Lemma 3.2 The proof consists of three parts: We first show that V (x) = X i∈X µi(xi/µi)−α (26) is the Lyapunov function of the ODE ˙x = π[x] − x
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:27.306312Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f808de21-24de-4051-bfa0-94741f3081c2 · outbound
This paper cites In our Algorithm 1, replacing the target of the base MCMC sampler from µ to π[x] results in an ergodic transition matrix P [x] parameterized by x, which is π[x]-invariant.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs In our Algorithm 1, replacing the target of the base MCMC sampler from µ to π[x] results in an ergodic transition matrix P [x] parameterized by x, which is π[x]-invariant
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:27.124141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d1f6e60b-f0f4-432b-9a3f-46e472855b70 · outbound
This paper cites tX s=1 Φ(θ∗, Zs) #.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs tX s=1 Φ(θ∗, Zs) #
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:26.890882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 48b48edb-2c04-463d-bc7c-37af196016ab · outbound
This paper cites For simulation setting, We run 50 independent trials with 300,000 steps and set one-third of the number of steps as burn-in period before collecting samples.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs For simulation setting, We run 50 independent trials with 300,000 steps and set one-third of the number of steps as burn-in period before collecting samples
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:24.676914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 755ef997-c82c-4770-b565-5d8582635895 · outbound
This paper cites More results on HDT-MCMC in graph sampling In this section, we present more simulation results on the algorithm that utilizes HDT-MCMC framework for graph sampling in other graph.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs More results on HDT-MCMC in graph sampling In this section, we present more simulation results on the algorithm that utilizes HDT-MCMC framework for graph sampling in other graph
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:25.962688Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6e21f810-bbde-44f9-bc94-85c49cdf177a · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:25.466335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ea8ae5ae-fd4a-4282-b833-1ec61b9f7545 · outbound
This paper cites Moreover, in p2p-Gnutella08 graph, we notice that the performance of LRU design is robust to the choice of the memory capacity.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Moreover, in p2p-Gnutella08 graph, we notice that the performance of LRU design is robust to the choice of the memory capacity
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:25.217080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1a328969-7a00-4f15-8cd2-6c1051be49ad · outbound
This paper cites 500 1000 1500 2000 2500 3000 Steps 0.4 0.5 0.6 0.7 0.8 0.9 1.0TVD WikiVote Graph MHRW MHRW-HDT ( = 0.5) MHRW-HDT ( =.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs 500 1000 1500 2000 2500 3000 Steps 0.4 0.5 0.6 0.7 0.8 0.9 1.0TVD WikiVote Graph MHRW MHRW-HDT ( = 0.5) MHRW-HDT ( =
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:24.935850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1d36ea98-f9ab-4c4a-b4e2-c6a7d3aafc46 · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:24.382418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 924e201b-7e32-432a-a2c2-6738242c1c04 · outbound
This paper cites an unresolved cited work.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T14:47:24.072460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 88c6f17a-f8cb-41e7-9032-494963c2d525 · outbound
This paper cites µi ∝ di with α = 1 in HDT.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs µi ∝ di with α = 1 in HDT
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:23.812921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 73f7afe6-8bdb-41db-bdcb-8abb81bddadf · outbound
This paper cites and Hwang, C.-R.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs and Hwang, C.-R
Reference 1999
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:28.853223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1dd23367-952b-4187-a045-545f447367a8 · outbound
This paper cites Irreversible Samplers from Jump and Continuous Markov Processes.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Irreversible Samplers from Jump and Continuous Markov Processes
Reference 2000
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:47:20.496664Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 841ba0c8-5812-4957-96df-6c7a0d0868b4 · outbound
This paper cites Revisiting Random Walks for Learning on Graphs.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Revisiting Random Walks for Learning on Graphs
Reference 2002
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:47:19.900181Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b92ba2e3-de76-45ad-9e30-0db38ec8e9a6 · outbound
This paper cites Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data
Reference 2005
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:47:20.148987Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6cb2536-060c-44d4-a04e-2486a75bb3c8 · outbound
This paper cites and Livingstone, S.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs and Livingstone, S
Reference 2007
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:29.117009Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c6e64264-d29b-4b41-9dc5-47463a87cb87 · outbound
This paper cites Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Nonreversible MCMC from conditional invertible transforms: a complete recipe with convergence guarantees
Reference 2010
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:47:20.905930Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 118bb033-3d2b-4ce6-adf2-3da046b4c1c0 · outbound
This paper cites Given a sequence of random variable θ1, θ2, · · ·with partial sum Sn ≜ Pn s=1 θs such that 1√n Sn n→∞ − − − − → dist.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Given a sequence of random variable θ1, θ2, · · ·with partial sum Sn ≜ Pn s=1 θs such that 1√n Sn n→∞ − − − − → dist
Reference 2013
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:26.670909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ed77960a-987a-49b6-894b-c6ebe57c179b · outbound
This paper cites Decentralized learning with random walks and communication-efficient adaptive optimization.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Decentralized learning with random walks and communication-efficient adaptive optimization
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:28.150981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation eb4c6855-2b72-40f0-afb3-f2cce5da54db · outbound
This paper cites Lifting Markov Chains To Mix Faster: Limits and Opportunities.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Lifting Markov Chains To Mix Faster: Limits and Opportunities
Reference 2021
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:47:23.587362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f399b553-03cb-4d0b-8c0c-2389563c8422 · outbound
This paper cites Matrix Form of Covariance Matrix (4) The multivariate version of Br´emaud (2013, eq.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Matrix Form of Covariance Matrix (4) The multivariate version of Br´emaud (2013, eq
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T14:47:27.724908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 33ea65b1-26cc-4c93-875b-3a4a39644406 · outbound
This paper cites Efficient Unbiased Sparsification.
Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs Efficient Unbiased Sparsification
Reference 2023
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T14:47:23.381639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
Observation 2fd3cb88-ea04-4cfb-a12b-4babd3f7ab94 · inbound
True Self-Avoiding Walk for Accelerating Markov-Chain Monte Carlo Integration cites this paper.
True Self-Avoiding Walk for Accelerating Markov-Chain Monte Carlo Integration Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:22:46.539577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.