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Paper Citation Record · LEDGER

Entity Cloze By Date: What LMs Know About Unseen Entities

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2205.02832.

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

pith.paper-citation-record.v1
2205.02832 v1

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:51:13.501992Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T20:46:51.605966Z

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 926e55d5-9c98-4f4a-81e5-5ca6df704205 · inbound

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models cites this paper.

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models Entity Cloze By Date: What LMs Know About Unseen Entities

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-12T14:51:13.501992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:51:13.501992Z digest=sha256:1e1692bdbc66e186b77e34b115e112868e02c8d667675d84b9d3698da8aa6213

Observation f0c4b5a9-c13b-4f17-a210-1cd754185b91 · inbound

Detecting Turkish Synonyms Used in Different Time Periods cites this paper.

Detecting Turkish Synonyms Used in Different Time Periods Entity Cloze By Date: What LMs Know About Unseen Entities

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T13:59:23.740219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:59:23.740219Z digest=sha256:a5807e6200a4487ccf8d464b60da097002d391c035ef4ee3418d5014bcc8c0fc

Observation 5062bf75-5c3d-4a34-8693-db90c50a0356 · inbound

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy cites this paper.

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy Entity Cloze By Date: What LMs Know About Unseen Entities

Reference 147

Resolution
unresolved
no resolver link, observed 2026-08-10T20:05:12.456365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:05:12.456365Z digest=sha256:59895ad33d9d644385c41eed88852ca838de44d96d516957f4caa7429f0333ee

Observation db6bc1ce-20f8-498e-a7d1-4395cceca1c4 · inbound

Principled Detection of Hallucinations in Large Language Models via Multiple Testing cites this paper.

Principled Detection of Hallucinations in Large Language Models via Multiple Testing Entity Cloze By Date: What LMs Know About Unseen Entities

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:46:51.609066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T20:44:52.898833Z digest=sha256:455381b8a5c8b6bdf36f0d3ae013d9296da81f8bb4ee19a15e95aabfc4723705

Observation c67ec331-c07f-4f3c-a7bc-b2187990be3c · inbound

Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain cites this paper.

Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain Entity Cloze By Date: What LMs Know About Unseen Entities

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-05T10:44:10.542462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:44:10.542462Z digest=sha256:e312f78de6a32454a8ec3d9042f082b934eb7089edc9ff6c70e829a6e44e832b