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Paper Citation Record · LEDGER

Unpacking Large Language Models with Conceptual Consistency

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.15093.

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

pith.paper-citation-record.v1
2209.15093 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T17:50:46.539215Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T17:51:54.928609Z

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 be13cee1-e19a-4db3-a929-f4a9469777cd · inbound

If Concept Bottlenecks are the Question, are Foundation Models the Answer? cites this paper.

If Concept Bottlenecks are the Question, are Foundation Models the Answer? Unpacking Large Language Models with Conceptual Consistency

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-22T17:51:54.931738Z

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=2026-05-22T17:50:46.539215Z digest=sha256:13dfe1d35d7406c453e055ec109e559b1734b7041ef31410a58996b670bfb9d0

Observation d0f4f850-c330-4b5a-84f8-f267ed04e3fd · inbound

Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations cites this paper.

Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations Unpacking Large Language Models with Conceptual Consistency

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:49:05.314631Z

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=2026-05-20T21:47:42.958875Z digest=sha256:33a77c143491703b624632eb28de76d4c7d05d8411f02ee3609a40332d50b1e7