Pith. sign in

Paper Citation Record · LEDGER

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics

As of 15 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 2 inbound Pith citation observations for arXiv:2506.21964.

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

pith.paper-citation-record.v1
2506.21964 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:18:19.694996Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T16:39:03.794436Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

26 of 26 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 81741660-5d10-4a2c-8b12-44b4f659f95c · outbound

This paper cites LLMs in Education: Novel Perspectives, Challenges, and Opportunities.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics LLMs in Education: Novel Perspectives, Challenges, and Opportunities

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:17.038047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:17.038047Z digest=sha256:e333e05d8978b5a7c5232d42a59abc60f83da157d45589ba690ad9fe264a5a56

Observation 2c012651-1833-4a87-a125-7948e654c417 · outbound

This paper cites Claude 3 Opus.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Claude 3 Opus

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:23.766208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:17.136528Z digest=sha256:524ede0bde313ad95230234fd941dda828872ae3ade20a38698c94af072cd8d9

Observation 36bbd8cd-a729-405c-9727-7b95992f6c17 · outbound

This paper cites Current applications and challenges in large language models for patient care: a systematic review.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Current applications and challenges in large language models for patient care: a systematic review

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:23.574770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:17.300893Z digest=sha256:5b5ca06cd364884e051be720be1350a927ee777c9ff5d4e72961399944782861

Observation d3310127-9360-4ec2-94ab-49795d5fd4bf · outbound

This paper cites AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:17.423686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:17.423686Z digest=sha256:fc5fc4b4cd74bd3d9c3baefbf26427ff37fe51d6a00851ec1383aa565758ee1b

Observation 77c30e93-5b50-4840-b919-7e03f0f01e00 · outbound

This paper cites Statistical inference.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Statistical inference

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:17.530924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:17.530924Z digest=sha256:e57ce1b23e838bc82916edaf8769cd498aa748686ddce4e4fc7f8d8571b6abfe

Observation 93b7dbb5-8f57-4120-9467-3c565f312ff1 · outbound

This paper cites Leveraging large language models in finance: Pathways to responsible adoption, 2024.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Leveraging large language models in finance: Pathways to responsible adoption, 2024

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:23.364282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:17.677896Z digest=sha256:03d94c23373d0d45691b55d39add204aae22e48fb432e245fbc00d5768b1fc1d

Observation e99bbb01-afc6-47a4-bdad-6bb1454ad725 · outbound

This paper cites Checking for prior-data conflict.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Checking for prior-data conflict

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:23.191995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:17.783419Z digest=sha256:1157bddbe8bd4b84246c822901c39e83987b42b9aa45d5367c9d86d4d0a0df1c

Observation 9a5a27ab-ac71-4551-92ac-eefebc4acd8a · outbound

This paper cites Bayesian concept bottleneck models with llm priors.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Bayesian concept bottleneck models with llm priors

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:17.886523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:17.886523Z digest=sha256:243a0428e8eeb2cd954f9c0540149272d947ffa042204fd99904432840b29c00

Observation ac663942-d202-45ba-ac56-e92bb33d284d · outbound

This paper cites Carlin, Hal S.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Carlin, Hal S

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:23.021473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:17.967917Z digest=sha256:47a1ed63275b66762a6e8223f5cc2c806b2e0a7cc910d3e3b9ad918255f6758f

Observation 05aa15ea-6357-4f55-b11b-da4444129804 · outbound

This paper cites Gemini 1.5 Pro.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Gemini 1.5 Pro

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:22.829107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.059908Z digest=sha256:8841d6ccd7ed12d64592d18dd8541da8573b66a5bb05ceeeadb024c4b387b2d1

Observation 8d7f2acb-3ca4-4ea3-b0ef-8ffad289ddc7 · outbound

This paper cites Automated prior elicitation from large language models for bayesian logistic regression.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Automated prior elicitation from large language models for bayesian logistic regression

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:22.683003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.161773Z digest=sha256:528f3aca0b1868f227e612f970f894445cce3caa8b3fe70abb034c72868b850c

Observation 85a53a13-f997-4b7a-8438-b45ecb470fa6 · outbound

This paper cites Accurate predictions on small data with a tabular foundation model.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Accurate predictions on small data with a tabular foundation model

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:22.515303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.229325Z digest=sha256:1c0861f33b9bc68d2fbf54f0ff2752b62ba5e83818dab064808ee839e0d180c9

Observation 4b8a6a6e-d9d9-4251-9c60-876aef9039f4 · outbound

This paper cites Heart Disease.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Heart Disease

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:18.285386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:18.285386Z digest=sha256:cf34b3c8587dae602306006d8641abc6b4b452be3bb320deeaa53567fcf4d601

Observation 74147a03-8fcb-4d27-952d-2f94ff2dba56 · outbound

This paper cites Survey of hallucination in natural language generation.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Survey of hallucination in natural language generation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:18.385658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:18.385658Z digest=sha256:f055fbbc351a4db8695d8b31c46bddfeb00eb8ab5031cf5c7bce28cfe7560a23

Observation b381ce0e-8908-45f3-b3c2-ecc78027e234 · outbound

This paper cites The Fram- ingham Heart Study and the epidemiology of cardiovascular diseases: a historical perspec- tive.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics The Fram- ingham Heart Study and the epidemiology of cardiovascular diseases: a historical perspec- tive

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:22.337544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.508744Z digest=sha256:c6fe03757942e78b51708cee747e47d80cb56a07ce4b519a97ef5a6f2773f635

Observation 66e2ef5c-6397-48b0-9597-7f6eb80fc662 · outbound

This paper cites Prior knowledge elicitation: The past, present, and future.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Prior knowledge elicitation: The past, present, and future

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:22.164242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.582216Z digest=sha256:454f68757a0f987fc44db23e101b92604d3e6b135af648a6dae3d7149635d1b2

Observation 85e0ee85-086d-42d1-acc3-9bb3dd99a5ed · outbound

This paper cites Inference for the generalization error.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Inference for the generalization error

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:21.973006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.703194Z digest=sha256:bdcc1dcc80e12c553c6c51893b1b3b1d3224c6afbf1f53db3daa8c5dff0a23cc

Observation c2c584e2-13d9-48e6-9534-066de14d56f3 · outbound

This paper cites A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:18.824699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:18.824699Z digest=sha256:b0b0b390d502894079dc24f460979aa2965630b0efcf627ba2d2d404f374b071

Observation a089c244-cf31-451e-91ee-feb32bc41b2e · outbound

This paper cites Checking for prior-data conflict using prior-to-posterior divergences.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Checking for prior-data conflict using prior-to-posterior divergences

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:21.761155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:18.931438Z digest=sha256:72021530d0bd30592d140115207db6a07ad4befc17011a4d72cef85ea7407e49

Observation 16d298f6-530c-4548-aea2-373c3caadab5 · outbound

This paper cites ChatGPT-4o-mini.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics ChatGPT-4o-mini

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:21.373608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:19.049344Z digest=sha256:ccfc849aa43094d1d435ccc6c4aedd8b733df171413d89be62709bf238e91f85

Observation ff923e51-7075-4a93-8e9e-cc5517bff25d · outbound

This paper cites Llm processes: Numerical predictive distributions conditioned on natural language.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Llm processes: Numerical predictive distributions conditioned on natural language

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:20.746507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:19.153004Z digest=sha256:f6a26407998f4dc4a216c949964ced5d0f86bad43aed25638518565c3267b05b

Observation 17ec953a-4a18-473d-b76a-fb52b4beff1c · outbound

This paper cites Approximate bayesian inference for latent gaussian models by using integrated nested laplace approximations.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Approximate bayesian inference for latent gaussian models by using integrated nested laplace approximations

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:20.540929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:19.277922Z digest=sha256:a85db6766ac45fb05964f41c38f8315b3b59d8d6489df4994888af35247131a5

Observation ce110da1-21e4-4571-ac96-30cdf06ccdbd · outbound

This paper cites MONICA: Monograph and Multimedia Sourcebook: World’s largest study of heart disease, stroke, risk factors, and population trends, 1979-2002.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics MONICA: Monograph and Multimedia Sourcebook: World’s largest study of heart disease, stroke, risk factors, and population trends, 1979-2002

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:20.273350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:19.441845Z digest=sha256:3879b42011f75e187d2660f4173338c768a16fa377befe41d7ff2cdff1dc1ae1

Observation ed148836-1467-44f8-9608-7a2771255ab5 · outbound

This paper cites Large Language Models for Education: A Survey and Outlook.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Large Language Models for Education: A Survey and Outlook

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:19.538903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:19.538903Z digest=sha256:3d4ff5a923376de34a26352f66f6e30adfd345f56a8d578a34da38629a1d90de

Observation d86305c0-44ce-4fbb-966b-316858a5572b · outbound

This paper cites Concrete Compressive Strength.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Concrete Compressive Strength

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T22:18:19.601918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:18:19.601918Z digest=sha256:5c21fc2349a75a7a2d24a8b157062ceebb7022d3a082567647600beebe244051

Observation 2501d4e7-5c7b-4f03-9966-af53f96c1942 · outbound

This paper cites Revolutionizing health care: The transforma- tive impact of large language models in medicine.

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics Revolutionizing health care: The transforma- tive impact of large language models in medicine

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:20.010877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T22:18:19.694996Z digest=sha256:15ddaa6da14217e783c75153155f43598752fffa6aebd096ea16016b5f6227f5

Pith citing papers

Observation 2b0ad765-4c16-432c-8d73-f167e32f3cd1 · inbound

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences cites this paper.

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics

Reference 104

Resolution
verified exact
arxiv_id, observed 2026-05-18T16:41:38.155199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T16:39:03.794436Z digest=sha256:fd0c873ab9e09ce6a5168017afcbda3f8ef142383f7dc12a85391be5e9f18070

Observation 3c564027-827c-4ccd-a1d0-3b92dc8268ae · inbound

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences cites this paper.

The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics

Reference 105

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T16:41:37.530277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T16:39:03.794436Z digest=sha256:b70f49892b316877e057b89d301ba4885b2aeb5ba9c6c737b417b11cb93b3a2b