Paper Citation Record · LEDGER

Universal priors: solving empirical Bayes via Bayesian inference and pretraining

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 4 inbound Pith citation observations for arXiv:2602.15136.

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

pith.paper-citation-record.v1
2602.15136 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:03:08.444115Z

measured 22 of 22 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T08:11:22.973978Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T07:29:39.501657Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cec5dd0b-0e82-4dda-bca9-7e1f2963e353 · outbound

This paper cites The Bayesian Geometry of Transformer Attention.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining The Bayesian Geometry of Transformer Attention

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:05.909471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d3171b4-363e-4e75-b8f9-dbcce074e9e7 · outbound

This paper cites Transformers Simulate MLE for Sequence Generation in Bayesian Networks.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Transformers Simulate MLE for Sequence Generation in Bayesian Networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.220395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 485328a3-3341-4ab0-80cf-a47d3d521e82 · outbound

This paper cites Learning Minimax Estimators via Online Learning.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Learning Minimax Estimators via Online Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.643921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41e686a6-1e97-4c6e-8216-d55b19cd35b3 · outbound

This paper cites Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.816797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cfa8f86-9323-4689-b09b-b5ce04028d79 · outbound

This paper cites Quantitative bounds for length generalization in transformers.arXiv preprint arXiv:2510.27015,.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Quantitative bounds for length generalization in transformers.arXiv preprint arXiv:2510.27015,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.071159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01b34881-3ecb-43d1-a0b5-a489f283bc81 · outbound

This paper cites In-Context Parametric Inference: Point or Distribution Estimators?.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining In-Context Parametric Inference: Point or Distribution Estimators?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.624315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07be77e3-042a-4b05-8294-d6fdb14f4cb5 · outbound

This paper cites A Survey on Practical Applications of Multi-Armed and Contextual Bandits.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining A Survey on Practical Applications of Multi-Armed and Contextual Bandits

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:08.024947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 183c3e76-4545-4b7e-8023-05f90ca6f11c · outbound

This paper cites Solving Empirical Bayes via Transformers.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Solving Empirical Bayes via Transformers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:08.310761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4ef6ee2-10e3-43c1-949f-70ce9c48904c · outbound

This paper cites Transformers Can Achieve Length Generalization But Not Robustly.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Transformers Can Achieve Length Generalization But Not Robustly

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:08.444115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d5c3fa0-5b79-42b6-8139-3d4bdd79dfa1 · outbound

This paper cites Epsilon-Minimax Solutions of Statistical Decision Problems.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Epsilon-Minimax Solutions of Statistical Decision Problems

Reference 1953

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.369815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a597387-113c-4d05-9e05-c8a2d645c337 · outbound

This paper cites Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?

Reference 1956

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:08.164630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c28667f3-3f74-434c-af89-fc9671160027 · outbound

This paper cites Amortized In-Context Bayesian Posterior Estimation.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Amortized In-Context Bayesian Posterior Estimation

Reference 1983

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.460954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3e7988d-7af3-472c-a999-b05d5ba32eb3 · outbound

This paper cites Stein’s unbi- ased risk estimate and Hyvärinen’s score matching.arXiv preprint arXiv:2502.20123,.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Stein’s unbi- ased risk estimate and Hyvärinen’s score matching.arXiv preprint arXiv:2502.20123,

Reference 2000

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.535334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a593ce-3f77-479b-9243-6de8f11be344 · outbound

This paper cites Function estimation in the empirical Bayes setting.arXiv preprint arXiv:2601.18689,.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Function estimation in the empirical Bayes setting.arXiv preprint arXiv:2601.18689,

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.304497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84190108-801a-44ec-8ad8-569f8aed154f · outbound

This paper cites A nonparametric regression alternative to empirical Bayes approaches to simultaneous estimation.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining A nonparametric regression alternative to empirical Bayes approaches to simultaneous estimation

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.117103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91dfd19f-eea4-4b61-83de-cfcdca62cc8b · outbound

This paper cites Tabdpt: Scaling tabular foundation models.arXiv preprint arXiv:2410.18164,.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Tabdpt: Scaling tabular foundation models.arXiv preprint arXiv:2410.18164,

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.717405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32aade56-2c37-4dd6-aa31-ba09d2b5c564 · outbound

This paper cites Sharp regret bounds for empirical Bayes and compound decision problems.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Sharp regret bounds for empirical Bayes and compound decision problems

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:07.847887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8226d218-d160-4205-96fe-8239edb51c8b · outbound

This paper cites On Provable Length and Compositional Generalization.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining On Provable Length and Compositional Generalization

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T23:03:06.012233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation b38e7a3f-4f5c-4c5c-8d67-82ee49757578 · inbound

Poisson Empirical Bayes via Gamma-Smoothed Nonparametric Maximum Likelihood cites this paper.

Poisson Empirical Bayes via Gamma-Smoothed Nonparametric Maximum Likelihood Universal priors: solving empirical Bayes via Bayesian inference and pretraining

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-23T04:13:44.680708Z

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.

Observation c65408e3-04fd-4eff-b380-6f72ef23c624 · inbound

Quasi-Bayes empirical Bayes estimation of sums of random variables cites this paper.

Quasi-Bayes empirical Bayes estimation of sums of random variables Universal priors: solving empirical Bayes via Bayesian inference and pretraining

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-04T07:29:39.502857Z

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.

Observation 15574225-b30d-405b-bfa2-557de0928b01 · inbound

Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions cites this paper.

Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions Universal priors: solving empirical Bayes via Bayesian inference and pretraining

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-03T07:27:43.815530Z

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.

Observation 6f4ae3e3-b7a3-48ca-a65c-baa965533e0e · inbound

Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions cites this paper.

Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions Universal priors: solving empirical Bayes via Bayesian inference and pretraining

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-12T08:11:22.973978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.