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Paper Citation Record · LEDGER

Entity Cloze By Date: What LMs Know About Unseen Entities

As of 19 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 2026-08-19T06:32:44.657259+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:d91a5dde45106da19b47cfae33c02e81722a2a3e458d3ba732f4a6f50db501aa

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=sha256:3171533944de9e4e856dc939a65ce1e5c417bf261b5adef817d0971c1a311677

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:f3dfb4662e5b83490582e32b9496b0fd9d369aea0cc57a97c8c1ed10970e36af

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-18T20:44:52.898833Z digest=sha256:51ebb306abd4d69d2503b6fbcfd5699dd0d7f8d30f514a06bffc6a6e42ca38dd

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=sha256:5d6871863884f04096b44aa919890c02684e5539f1230d51a1672fb8658befa9