Paper Citation Record · LEDGER

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior

As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.03444.

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

pith.paper-citation-record.v1
2506.03444 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:09:29.894690Z

measured 33 of 33 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

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

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Outbound references

Observation 1519a35d-ee83-4447-a436-09fd75c3ccdb · outbound

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

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 1

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Observation 4545f5c6-9cc5-43d3-8b2c-e27cf42cd131 · outbound

This paper cites Data polygamy: The many-many relationships among urban spatio-temporal data sets.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Data polygamy: The many-many relationships among urban spatio-temporal data sets

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:33.439574Z

Source-reported events for the cited work

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Observation 5455087d-2fb9-4e0b-916e-ece31bcb3be4 · outbound

This paper cites LMPriors: Pre-Trained Language Models as Task-Specific Priors.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior LMPriors: Pre-Trained Language Models as Task-Specific Priors

Reference 3

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Observation 129c3d47-ac7a-4653-8ecb-156077ae3f78 · outbound

This paper cites Exploratory data analysis.Secondary analysis of electronic health records, pages 185–203, 2016.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Exploratory data analysis.Secondary analysis of electronic health records, pages 185–203, 2016

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:33.251288Z

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Observation 27f529ad-e93e-4fe7-9c50-17ebba513e68 · outbound

This paper cites Aleatory or epistemic? does it matter?Structural Safety, 31(2):105–112, 2009.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Aleatory or epistemic? does it matter?Structural Safety, 31(2):105–112, 2009

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:33.028909Z

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Observation 7739477a-e6c7-4504-af4f-640bfec6b715 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 6

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Observation c73e2483-6699-44c4-be99-efe91b2e1b25 · outbound

This paper cites Riding tandem: Does cycling infrastructure investment mirror gentrification and privilege in portland, or and chicago, il? Research in Transportation Economics, 60:14–24, 2016.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Riding tandem: Does cycling infrastructure investment mirror gentrification and privilege in portland, or and chicago, il? Research in Transportation Economics, 60:14–24, 2016

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:32.812379Z

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Observation 92b695e9-110b-42e9-8eb4-01efae95338c · outbound

This paper cites Nexus: Correlation discovery over collections of spatio-temporal tabular data.Proc.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Nexus: Correlation discovery over collections of spatio-temporal tabular data.Proc

Reference 8

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Observation ce808719-2390-4757-8d8d-3eb01b9efe51 · outbound

This paper cites Shelf: the sheffield elicitation framework.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Shelf: the sheffield elicitation framework

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:32.591769Z

Source-reported events for the cited work

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Observation f0ea8bc0-b579-413b-8795-5bd807b52f75 · outbound

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

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Automated prior elicitation from large language models for bayesian logistic regression

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:32.344192Z

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 ed202021-b835-4ccf-b264-0e6f974ed61f · outbound

This paper cites Big data: A revolution that will transform how we live, work, and think, 2014.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Big data: A revolution that will transform how we live, work, and think, 2014

Reference 11

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Observation 27bfbecb-be4f-4fe5-84b7-11eede560333 · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? InNeurIPS, 2017.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior What uncertainties do we need in bayesian deep learning for computer vision? InNeurIPS, 2017

Reference 12

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Observation 5e167cf9-f9a4-4a76-a146-84b8520c6d9e · outbound

This paper cites Biograph: unsupervised biomedical knowledge discovery via automated hypothesis generation.Genome biology, 12:1–12, 2011.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Biograph: unsupervised biomedical knowledge discovery via automated hypothesis generation.Genome biology, 12:1–12, 2011

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:31.903950Z

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Observation d253c238-a379-485d-9886-22a6ae4cdc4d · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 14

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Observation eaa3c2bc-8513-4cea-9492-dc62a42f4e75 · outbound

This paper cites Distinguishing cause from effect using observational data: methods and benchmarks.Journal of Machine Learning Research, 17(32):1–102, 2016.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Distinguishing cause from effect using observational data: methods and benchmarks.Journal of Machine Learning Research, 17(32):1–102, 2016

Reference 15

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Observation 78bdb5e7-6c04-4824-8ae9-cfe565e2c651 · outbound

This paper cites John Wiley & Sons, 2006.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior John Wiley & Sons, 2006

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:31.576909Z

Source-reported events for the cited work

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Observation fcac3002-9b65-460b-b818-5ef30c380ea3 · outbound

This paper cites an unresolved cited work.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:09:31.414997Z

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Observation 3b052819-c039-4fe6-b69e-d005ae3cb141 · outbound

This paper cites Language Models as Knowledge Bases?.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Language Models as Knowledge Bases?

Reference 18

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Observation a614afb0-e817-40c0-a141-221046daa43b · outbound

This paper cites Chicago data portal, 2025.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Chicago data portal, 2025

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:31.263249Z

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Observation 03e6a59e-89df-40d8-8c5d-4ac9eb1db5a6 · outbound

This paper cites Llm processes: Numerical predictive distributions conditioned on natural language.Advances in Neural Information Processing Systems, 37:109609–109671, 2024.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Llm processes: Numerical predictive distributions conditioned on natural language.Advances in Neural Information Processing Systems, 37:109609–109671, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:31.102639Z

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Observation b1c53de9-cb5e-4eb1-9bf8-76f945008e47 · outbound

This paper cites Correla- tion sketches for approximate join-correlation queries.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Correla- tion sketches for approximate join-correlation queries

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:31.020007Z

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Observation ef96b2f6-d8df-4a62-86f0-53abe1272011 · outbound

This paper cites Efficiently estimating mutual information between attributes across tables.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Efficiently estimating mutual information between attributes across tables

Reference 22

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This paper cites John Wiley & Sons, 2015.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior John Wiley & Sons, 2015

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:30.918857Z

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Observation 7c567d40-19e9-4578-929f-ef42f710c95f · outbound

This paper cites A mathematical theory of communication.The Bell system technical journal, 27(3):379–423, 1948.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior A mathematical theory of communication.The Bell system technical journal, 27(3):379–423, 1948

Reference 24

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This paper cites Directlingam: A direct method for learning a linear non-gaussian structural equation model.Journal of Machine Learning Research-JMLR, 12(Apr):1225–1248, 2011.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Directlingam: A direct method for learning a linear non-gaussian structural equation model.Journal of Machine Learning Research-JMLR, 12(Apr):1225–1248, 2011

Reference 25

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This paper cites Routledge, 2018.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Routledge, 2018

Reference 26

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Observation e19fbf49-0ad5-41f3-a7ca-756c2365b362 · outbound

This paper cites Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023

Reference 27

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Observation 360ea4b0-ffdf-4ace-b772-f00405ddf0b5 · outbound

This paper cites Statistical methods, 8thedn.Ames: Iowa State Univ.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Statistical methods, 8thedn.Ames: Iowa State Univ

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:09:30.758798Z

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Observation 0f52ba28-d96b-4ef3-be3c-93ce8f0ab509 · outbound

This paper cites Wilkins, Benjamin J.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Wilkins, Benjamin J

Reference 29

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This paper cites Can large language models predict data correlations from column names? Proc.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Can large language models predict data correlations from column names? Proc

Reference 30

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Observation 54597817-6620-419a-bb2b-28ff9096612c · outbound

This paper cites Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:29.837731Z

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Observation e6707d9b-8f75-49d8-ab75-4473d40597fe · outbound

This paper cites Large language models for scientific discovery in molecular property prediction.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior Large language models for scientific discovery in molecular property prediction

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:29.865282Z

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Observation f6cce9c3-1f1f-43ab-9636-28d3c16f07a4 · outbound

This paper cites coefficient.

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior coefficient

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:29.894690Z

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Pith citing papers

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