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Paper Citation Record · LEDGER

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models

As of 10 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 1 inbound Pith citation observation for arXiv:2604.26029.

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

pith.paper-citation-record.v1
2604.26029 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-07T15:08:00.020977Z

measured 8 of 8 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T15:49:33.410214Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

7 of 7 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2703970-d858-4bae-8f7d-b93cd796067a · outbound

This paper cites Scalable and Calibrated Sampling for Bayesian Generalized Linear Mixed Model via Stochastic Gradient Markov Chain Monte Carlo.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Scalable and Calibrated Sampling for Bayesian Generalized Linear Mixed Model via Stochastic Gradient Markov Chain Monte Carlo

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:17:02.359214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:54e6215b1eb5d8584cd4620b6ec1538349af3082c7d9129f12c58d70ec3640f8

Observation 0004db1c-af73-4380-906f-bd374afd86b9 · outbound

This paper cites Fast and accurate binary response mixed model analysis via expectation propagation.Journal of the American Statistical Association, 115(532):1902–1916.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Fast and accurate binary response mixed model analysis via expectation propagation.Journal of the American Statistical Association, 115(532):1902–1916

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-27T03:48:45.425442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:1bc569eecf3cdb74fd091b7bf952513efbed9062b5c293a7ef70def6ac091f82

Observation 8b4d9f0d-3bb6-4146-950c-fc25d3b76775 · outbound

This paper cites Tables and Figures Table 1.Some commonly used GLMM specifications.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Tables and Figures Table 1.Some commonly used GLMM specifications

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-05-27T03:48:45.414105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:8907e00c9e994abc965b2517d1b6f9c7eee5087fd7190ec68450c0fcc6ee1bce

Observation c904baaf-0202-48aa-9b57-170c0b6c62f5 · outbound

This paper cites an unresolved cited work.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-05-27T03:48:45.422330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:51ccd3ce1980442965bf6631309ea703591472dd89550fa915a164b94c253f42

Observation 69349af2-b675-4b05-99a1-ea2e391c02e5 · outbound

This paper cites an unresolved cited work.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-05-27T03:48:45.418633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:43f2296bed595fe231ccc3afebcf0c75061aebc58ad5db3e174dd6f1416f1629

Observation 2d2693af-80f6-444b-b7bc-18829f4df48b · outbound

This paper cites Consider two Markov chains ϑ(1) k , ϑ(2) k evolving according to (7), with ϑ(1) k ∼ρ k and ϑ(2) k ∼˜ρk for each k.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Consider two Markov chains ϑ(1) k , ϑ(2) k evolving according to (7), with ϑ(1) k ∼ρ k and ϑ(2) k ∼˜ρk for each k

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-27T03:48:45.429224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:b37a1632615f2d446ba7fa42b4bc8fa8082de3174a6c6db3e12e8d0848f0e5e3

Observation 9216ffb6-c3c8-4e30-abcf-3dffb7dc02d6 · outbound

This paper cites an unresolved cited work.

Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-05-27T03:48:45.410405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T15:08:00.020977Z digest=sha256:856160f9a028e43c29d664adc9aee6b1d32efa8e189d916d7611fb3445b2cd3d

Pith citing papers

Observation 2f074390-65ae-473e-acab-2a3d94c1c7b5 · inbound

Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data cites this paper.

Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data Safe, Scalable, and Accurate Bayes Posterior Sampling for Large-Data Generalized Linear Mixed Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-11T15:49:33.410214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T15:49:33.410214Z digest=sha256:20b0ab530c26d0c32acdc5052da348f9a9e25548dfe10122add1e0de2b3f7745