Paper Citation Record · LEDGER

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data

As of 13 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2506.08750.

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

pith.paper-citation-record.v1
2506.08750 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:05:37.599085Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy4
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation be0f4bf1-7bbb-4f90-b65d-7aa040fbead4 · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:38.743483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d3e60344-41b7-44a0-b748-620326e63b6b · outbound

This paper cites They can revolutionize information retrieval, knowledge management, and even decision support systems.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data They can revolutionize information retrieval, knowledge management, and even decision support systems

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.591164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6f6adce-b76f-4f4c-8656-e7866307b97a · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:38.451802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5cb918e8-2e22-45e6-95c0-6a64ea88359a · outbound

This paper cites Essential CANDU.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Essential CANDU

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.321756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 537b9f0c-df1c-46cb-949f-ceb5e451306e · outbound

This paper cites We assess the quality of these pairs along several dimensions: semantic diversity, relevance to the source text, and overall question quality.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data We assess the quality of these pairs along several dimensions: semantic diversity, relevance to the source text, and overall question quality

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.192642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0f00c3e0-8635-4ff3-928a-68d742143409 · outbound

This paper cites Automated synthetic data collection must be prioritized to develop robust pipelines for large -scale gathering and structuring of synthetic nuclear QnA pairs.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Automated synthetic data collection must be prioritized to develop robust pipelines for large -scale gathering and structuring of synthetic nuclear QnA pairs

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:05:38.056986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 74a28746-b529-4e7b-82d3-680bbce1e14a · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:37.926350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 574188a8-7994-4b1b-aa44-c4fafaf13b44 · outbound

This paper cites On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.118238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 053bcf55-ffa2-4b46-80cf-249b35f1821b · outbound

This paper cites Best Practices and Lessons Learned on Synthetic Data.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Best Practices and Lessons Learned on Synthetic Data

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.206170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64f0ac7b-67a3-4168-9dd8-aaba76e07464 · outbound

This paper cites Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.301712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a95e756-72b9-4005-8208-a79b4acd093f · outbound

This paper cites RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.388116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d177d54-1935-4f31-9909-7737b8546399 · outbound

This paper cites DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.446229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a04ced7-f87a-4570-9681-90d20544b728 · outbound

This paper cites Synthetic Data Generation with Large Language Models for Personalized Community Question Answering.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Synthetic Data Generation with Large Language Models for Personalized Community Question Answering

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.497741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86b13bbf-fe94-4294-8a33-7bacd3cc55b9 · outbound

This paper cites Synthetic Data Generation with LLM for Improved Depression Prediction.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Synthetic Data Generation with LLM for Improved Depression Prediction

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:37.548832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d4a3b63-c7ba-449e-ab02-131cc27dafe8 · outbound

This paper cites an unresolved cited work.

Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:05:37.794215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.