Pith. sign in

Paper Citation Record · LEDGER

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data

As of 19 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 1 inbound Pith citation observation for arXiv:2508.20525.

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

pith.paper-citation-record.v1
2508.20525 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:47:34.948237Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T11:41:26.274423Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T11:44:09.291884Z

Reference resolution

11 of 11 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21cd5f54-23c2-4adc-a6c3-572ad411546b · outbound

This paper cites Explainable automated fact-checking for public health claims.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Explainable automated fact-checking for public health claims

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.888277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.888277Z digest=sha256:ffb7e22b6cf6970fe69675722429fdfe3644e3dc94fa0a7c6aa07fc99f11b6db

Observation 82604cff-fca4-4c42-8d8f-f6d46a5666dc · outbound

This paper cites Fact checking: Task definition and dataset construction.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Fact checking: Task definition and dataset construction

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.894100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.894100Z digest=sha256:33df9a980bdaa53dba3c891a2777a6638cd408484402f4dfc7d2c384c459fe06

Observation 65a9fb57-9704-4cd5-a91c-8518f7f6a61e · outbound

This paper cites Waszak, Wioleta Kasprzycka-Waszak, and Alicja Kubanek.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Waszak, Wioleta Kasprzycka-Waszak, and Alicja Kubanek

Reference 3

Resolution
verified exact
doi, observed 2026-08-15T16:47:35.077627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T16:47:34.899978Z digest=sha256:df7a2d4159c2bb5d1b989e0ccbecc297ac99f105113487348e5dfa09fe2a85e1

Observation e46588f1-45f3-4d3c-a8d1-c5ab1d44ff4d · outbound

This paper cites Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Scaling Public Health Text Annotation: Zero-Shot Learning vs. Crowdsourcing for Improved Efficiency and Labeling Accuracy

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:47:35.150968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T16:47:34.905497Z digest=sha256:c271d21850b2bec4b020197cca68c15690ca94752b6405d0ee9c98b07972915f

Observation 1d698f51-f1d0-4ebb-a93c-32ffa379a93b · outbound

This paper cites FEVER: A Large-Scale Dataset for Fact Extraction and VERification.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data FEVER: A Large-Scale Dataset for Fact Extraction and VERification

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.912202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.912202Z digest=sha256:480a7fd3c023badcb068a588a73a0aae18897195c68f735928caa81544e93434

Observation 2cf801aa-56e5-4bef-915c-67f3430e040a · outbound

This paper cites Fact or fiction: Verifying scientific claims.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Fact or fiction: Verifying scientific claims

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.919319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.919319Z digest=sha256:ab25210e70e0adbbf323f3b43496902ade5a50918ada7c47209312a91d73c71f

Observation 45e305b6-6264-4b5b-8e5f-ffaba4253b1e · outbound

This paper cites MiniCheck : Efficient fact-checking of LLMs on grounding documents.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data MiniCheck : Efficient fact-checking of LLMs on grounding documents

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.925360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.925360Z digest=sha256:7d2488968e5beba8cb4fb58363144c224f80497a0f925bc5efcd2a1366656d16

Observation 7cfaa355-3d04-462a-b235-ca534ee15086 · outbound

This paper cites FActScore : Fine-grained atomic evaluation of factual precision in long form text generation.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data FActScore : Fine-grained atomic evaluation of factual precision in long form text generation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.931454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.931454Z digest=sha256:66374cf103e8aec86198c2ffc2bb710fffd5829d366562cda07fb4a587d39d8f

Observation 1d13057b-d0da-4d91-97f9-baa2863f9a3f · outbound

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

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:47:35.208557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T16:47:34.937962Z digest=sha256:3b3aea167152fc09a107027ade036ea9fe20d137586561fd4ede13283bdaa77b

Observation 5994d6f1-1234-4c41-a662-2414d26220d0 · outbound

This paper cites A paragraph-level multi-task learning model for scientific fact-verification.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data A paragraph-level multi-task learning model for scientific fact-verification

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:47:35.188692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-15T16:47:34.942975Z digest=sha256:1d517f44c1a76b224a4f603a58b4f62d59df80f8b31b3e3123785a0c9e37b955

Observation a9ab059e-5115-4235-8b31-1b1d6957645f · outbound

This paper cites write newline.

Enhancing Health Fact-Checking with LLM-Generated Synthetic Data write newline

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T16:47:34.948237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:47:34.948237Z digest=sha256:85b08eb68a635e186582658814c2eb42c9b57c2ac80f1d0ca2d44251c1f366e0

Pith citing papers

Observation 56777979-4b31-4025-ad3f-83a8d779ab84 · inbound

Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attribution cites this paper.

Med-V1: Small Language Models for Zero-shot and Scalable Biomedical Evidence Attribution Enhancing Health Fact-Checking with LLM-Generated Synthetic Data

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-21T11:44:09.293635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-21T11:41:26.274423Z digest=sha256:c7788b6fd1065328669c8a43723714f2657d1f785a293df37e6778b17737e57f