Paper Citation Record · LEDGER

Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.10235.

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

pith.paper-citation-record.v1
2305.10235 v4

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 2026-08-10T12:52:24.554649Z

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

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

13
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fa2c6106-497d-45cf-904c-2460116fd13a · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 266

Resolution: verified exact; arxiv_id, observed 2026-05-18T11:17:08.768188Z

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 e5a2bd5e-7594-45f6-8e14-b6d8470d181c · inbound

Explaining GitHub Actions Failures with Large Language Models: Challenges, Insights, and Limitations cites this paper.

Explaining GitHub Actions Failures with Large Language Models: Challenges, Insights, and Limitations Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T12:52:24.554649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f17e0bc1-e48f-4aac-ab21-9c93e8167193 · inbound

Linearly Decoding Refused Knowledge in Aligned Language Models cites this paper.

Linearly Decoding Refused Knowledge in Aligned Language Models Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T21:27:35.020100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6aad6d91-519d-4a76-ad5f-2a5e53c6c458 · inbound

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models cites this paper.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:26:58.094112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e70c491-ed7e-47c2-aee6-a0d6b9a89ea8 · inbound

CASCADE: Detecting Inconsistencies between Code and Documentation with Automatic Test Generation cites this paper.

CASCADE: Detecting Inconsistencies between Code and Documentation with Automatic Test Generation Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-10T02:48:26.613169Z

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 2c6c2b02-85a9-4cd2-8657-9de35fee8995 · inbound

Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models cites this paper.

Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:26:09.203352Z

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.