Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 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 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:27:35.020100Z

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:b5381244e0041a69da50a9d1aba222e7adfe64175bf6d564fc6ab62009f69948

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.

source=pdf_text observed=2026-08-06T21:27:35.020100Z digest=sha256:a2e90e09ff8177e8a190d1dcc31a4ec4cd3c22196bd5a83eadd8eba1c8fc9a6c

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.

source=pdf_text observed=2026-08-06T17:26:58.094112Z digest=sha256:3972ad2cfcd9bff6bad8f08ec6d8c2b8c1765fee6ab1398cc70307b5e66bcaf3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T02:47:29.812338Z digest=sha256:583a9a24824a4897d814f9febbd2d2db88c13b4a58faf6eab263b09d4502b60d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T09:14:12.034025Z digest=sha256:96e0ad4a9a583ec9dd60110d6447b94d00d61a9d8a4d7f4465900c39726ed2f7