Paper Citation Record · LEDGER

Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2402.07401.

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

pith.paper-citation-record.v1
2402.07401 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:00:25.040828Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T16:14:53.347282Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d4360884-1e60-4b85-87b2-3f79429a9667 · inbound

Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-22T21:52:10.147985Z

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 5d76203e-21a4-4333-9880-11c17ea751c0 · inbound

EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actions cites this paper.

EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actions Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:00:25.040828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40bf87cb-0288-42fc-af4a-d8ee532e8112 · inbound

Multimedia Verification Through Multi-Agent Deep Research Multimodal Large Language Models cites this paper.

Multimedia Verification Through Multi-Agent Deep Research Multimodal Large Language Models Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T19:51:42.248959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84720870-bf70-414f-b739-f28de0d78088 · inbound

Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents cites this paper.

Debating Truth: Debate-driven Claim Verification with Multiple Large Language Model Agents Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:52:56.567874Z

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 207a5d6d-65c5-4851-9185-d9f0bd2b04ad · inbound

RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild cites this paper.

RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:31:13.350143Z

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 70a01c0c-decc-435a-b677-a4a81d8dac07 · inbound

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives cites this paper.

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 150

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T01:04:50.330378Z

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 c93445c5-0346-4ce9-adf9-430d7f284754 · inbound

RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild cites this paper.

RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wild Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:25.693840Z

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 f7d81b8c-3498-4237-9471-08763c42e4d4 · inbound

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models cites this paper.

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:15:20.098538Z

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 d46f0613-fa2d-4c08-a773-a54bf1b92075 · inbound

ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models cites this paper.

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:14:53.349076Z

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.