Paper Citation Record · LEDGER

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

As of 22 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 7 inbound Pith citation observations for arXiv:2411.17284.

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

pith.paper-citation-record.v1
2411.17284 v5

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:22:44.944142Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:57:38.058612Z

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

20 of 20 outbound references displayed

verified exact0
verified fuzzy8
unresolved11
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 7f2fcb44-1356-4c6b-b176-2b5e23c3781c · outbound

This paper cites As part of this, provide descriptive features and target names.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling As part of this, provide descriptive features and target names

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.204753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 63c01c92-f13f-4796-9aee-c6eb062bb5ad · outbound

This paper cites In our experiments, we asked the language model to rephrase both descriptions 10 times for each.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling In our experiments, we asked the language model to rephrase both descriptions 10 times for each

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.192688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2a932de1-c7ad-401c-ba06-14d2f2b87032 · outbound

This paper cites For each of the unique system and user role combinations, record the mean and standard deviation of the Gaussian prior elicited from the language model.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling For each of the unique system and user role combinations, record the mean and standard deviation of the Gaussian prior elicited from the language model

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.180451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 59dd8c1d-9027-4215-8555-bd3b15942309 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.168913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3a579f1b-0d4d-4896-8a7c-befef87cdbee · outbound

This paper cites Functions for doing this are provided in the supplementary code.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Functions for doing this are provided in the supplementary code

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.157775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 193e4f8b-d696-4b57-b31e-6dc6ce8ba8a1 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.146456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a3f92ee2-8a89-4c3b-91df-dea5bdd27179 · outbound

This paper cites With this new set of descriptions, again ask a language model to rephrase them.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling With this new set of descriptions, again ask a language model to rephrase them

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.134242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7252aaeb-f68f-4964-bd34-ac42c76b4ddd · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.123490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9b08a75e-cc9b-466f-bc26-6694c1b43082 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.111956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9884ea38-7073-484e-8faf-32e97992d37e · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.100889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fcea27d0-7989-4f75-b0e2-b27ebe68a427 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.089034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2b6d21df-f1c6-4a1d-9839-91b9a469aca6 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.076058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3386f780-e821-4d07-b468-26f4906475fc · outbound

This paper cites For the classification case, this is done more easily if the language model is asked to provide the probability of a positive prediction rather than the pre- diction itself.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling For the classification case, this is done more easily if the language model is asked to provide the probability of a positive prediction rather than the pre- diction itself

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.064257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f5a57fc9-0386-4b43-a934-8f3ccb6b3687 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.051663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6645d982-a345-4e62-a6c5-2888de1ecf15 · outbound

This paper cites For our experiments, we used a Gaussian kernel density estimator with a bandwidth factor of 0.25.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling For our experiments, we used a Gaussian kernel density estimator with a bandwidth factor of 0.25

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.040311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 55512664-058c-457c-a341-e2df3ee44a42 · outbound

This paper cites an unresolved cited work.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-12T12:22:45.027310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3021f3c5-aa5d-48e2-83e5-66a8ad581439 · outbound

This paper cites The target is linear in features.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling The target is linear in features

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:22:45.014746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8fd729ac-522e-4f46-9dbf-e95e5a88e6a5 · outbound

This paper cites Scaling Scaling Laws with Board Games.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Scaling Scaling Laws with Board Games

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T12:22:44.862596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44ab41de-fab2-4e50-9df8-5685b5d69ab9 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling A Comprehensive Overview of Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-12T12:22:44.868468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 023fa658-2b37-46e0-a77d-796e875e83f5 · outbound

This paper cites Eliciting the Priors of Large Language Models using Iterated In-Context Learning.

AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling Eliciting the Priors of Large Language Models using Iterated In-Context Learning

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-12T12:22:44.873093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9edd798b-3440-44c4-b33b-8cb91d5eb816 · inbound

Steering Risk Preferences in Large Language Models by Aligning Behavioral and Neural Representations cites this paper.

Steering Risk Preferences in Large Language Models by Aligning Behavioral and Neural Representations AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:57:38.058612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Exploiting LLMs for Automatic Hypothesis Assessment via a Logit-Based Calibrated Prior cites this paper.

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

Resolution: unresolved; no resolver link, observed 2026-08-07T11:09:26.348509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics cites this paper.

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.

Observation ec84e95e-e408-47cd-8d08-704c4cb6dfc5 · 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 AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:41:37.969845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c2532ae-10ac-4d46-93aa-4083d12f3bf3 · 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 AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 47

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T16:41:37.301455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3538f86a-0327-4a59-96c2-f3017d1b82c3 · inbound

AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers cites this paper.

AI4BayesCode: From Natural Language Descriptions to Validated Modular Stateful Bayesian Samplers AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:57:57.660378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0b621bc2-a433-4408-8b94-c2e297c432be · inbound

Causal Risk Minimization for High-Dimensional Treatments cites this paper.

Causal Risk Minimization for High-Dimensional Treatments AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:13:48.461829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.