Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.17120.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:15:17.872249Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T19:57:46.092792Z
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 edb1e5e7-3608-478f-8b80-6b770f8fada6 · inbound
Do we really have to filter out random noise in pre-training data for language models? cites this paper.
Do we really have to filter out random noise in pre-training data for language models? Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs
Reference 74
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T15:04:29.664691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9fe14b01-8e3b-469a-bccb-e119f8d9a787 · inbound
Has My System Prompt Been Used? Large Language Model Prompt Membership Inference cites this paper.
Has My System Prompt Been Used? Large Language Model Prompt Membership Inference Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T19:57:46.100489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b0a80150-14c7-4709-b5a4-c1c82104d113 · inbound
Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens cites this paper.
Beyond Semantics: The Unreasonable Effectiveness of Reasonless Intermediate Tokens Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:15:17.872249Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.