Paper Citation Record · LEDGER

Faithfulness Tests for Natural Language Explanations

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.18029.

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

pith.paper-citation-record.v1
2305.18029 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:22:23.149622Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T01:03:52.949391Z

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 928c8884-50c5-40a2-a549-dce28a816e2b · inbound

On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI cites this paper.

On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI Faithfulness Tests for Natural Language Explanations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T10:22:23.149622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c877e8ca-d434-4b45-a792-6b23e27f6ff8 · inbound

Rethinking Human Preference Evaluation of LLM Rationales cites this paper.

Rethinking Human Preference Evaluation of LLM Rationales Faithfulness Tests for Natural Language Explanations

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T17:15:27.857734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cb4aeb8-410b-4f4c-a6ca-1bd86f617d65 · inbound

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold cites this paper.

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold Faithfulness Tests for Natural Language Explanations

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:00:29.121065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b3c0ab89-f055-44da-8dd0-73f3baea63f5 · inbound

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold cites this paper.

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold Faithfulness Tests for Natural Language Explanations

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-21T01:03:52.951279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 04b19a20-51f5-457e-884e-f5fa1754bc73 · inbound

Faithfulness Serum: Mitigating the Faithfulness Gap in Textual Explanations of LLM Decisions via Attribution Guidance cites this paper.

Faithfulness Serum: Mitigating the Faithfulness Gap in Textual Explanations of LLM Decisions via Attribution Guidance Faithfulness Tests for Natural Language Explanations

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:36:02.822048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5a4ff46-5ac5-49bc-8d6b-6716660d588a · inbound

Training Large Language Models for Self-Explanation Faithfulness cites this paper.

Training Large Language Models for Self-Explanation Faithfulness Faithfulness Tests for Natural Language Explanations

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-01T08:36:25.462705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.