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Paper Citation Record · LEDGER

COPEN: Probing Conceptual Knowledge in Pre-trained Language Models

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.04079.

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

pith.paper-citation-record.v1
2211.04079 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T02:21:12.882825Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T02:21:16.256348Z

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 1d848ef5-d341-47c3-ab09-d18c7b479dc0 · inbound

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs cites this paper.

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs COPEN: Probing Conceptual Knowledge in Pre-trained Language Models

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:41:02.239107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-10T15:23:53.906870Z digest=sha256:81c61161dd98eca71c95e7da61f5e264eb1641cae946b2536db027694a6116e6

Observation 9a5a1847-6b53-4061-8bfe-ecbe430088a6 · inbound

Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents cites this paper.

Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents COPEN: Probing Conceptual Knowledge in Pre-trained Language Models

Reference 124

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:21:16.258041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T02:21:12.882825Z digest=sha256:d0c43978cf731009bb65213596ec982b02591e519a78067bc77cb09c594652ad