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Paper Citation Record · LEDGER

Evaluating the Robustness of Analogical Reasoning in Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2411.14215.

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

pith.paper-citation-record.v1
2411.14215 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:10:32.572118Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:28:58.093447Z

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 86f4fb34-241e-452a-8ee5-9011c9417d3c · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 86

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:32:33.270067Z

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=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:caa43bbec5978cf5e917a2bc88034db05e2c355c40a5d077315ddba39596dda6

Observation c1938ca5-e950-4a21-b155-715664967264 · inbound

Mechanistic Interpretability Needs Philosophy cites this paper.

Mechanistic Interpretability Needs Philosophy Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T23:50:47.367863Z

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=2026-05-21T23:49:19.683025Z digest=sha256:ec52ed8c34ca2ef97ee79a0543b6e0c7ceaf3feffab4b17c6da1838efb24bd64

Observation d87c7968-9b19-4564-bd8b-cbfae4473aab · inbound

Large Language Models Show Signs of Alignment with Human Neurocognition During Abstract Reasoning cites this paper.

Large Language Models Show Signs of Alignment with Human Neurocognition During Abstract Reasoning Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T21:10:32.572118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T21:10:32.572118Z digest=sha256:ce3285475efd7746fe966d79dfdc35488aeb1b1cc068910094f92790cf1be0ee

Observation 25a96312-2b0b-475c-91b2-649f60b911e9 · inbound

On Robustness and Reliability of Benchmark-Based Evaluation of LLMs cites this paper.

On Robustness and Reliability of Benchmark-Based Evaluation of LLMs Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T10:31:02.177268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:31:02.177268Z digest=sha256:95d09b846e22bc38da2711c69b63d03f801d0d8e92c79a113a515f06271dd751

Observation a0322c30-3942-409f-a309-44e1e89970ea · inbound

Can Large Language Models Generalize Procedures Across Representations? cites this paper.

Can Large Language Models Generalize Procedures Across Representations? Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T05:00:57.477973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T05:00:57.477973Z digest=sha256:5c3567433df91ab868c019df00f09f5d55617f426277d06af4fe2ff772a5723e

Observation 838842db-da98-4aa3-9e63-08afcba0ecf0 · inbound

Structural Ranking of the Cognitive Plausibility of Computational Models of Analogy and Metaphors with the Minimal Cognitive Grid cites this paper.

Structural Ranking of the Cognitive Plausibility of Computational Models of Analogy and Metaphors with the Minimal Cognitive Grid Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 225

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:56:06.210285Z

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=arxiv_source observed=2026-05-09T14:33:11.033906Z digest=sha256:5f35a5f7c50e4600908f63b3c69ae8fc2a7ee2ad56c19befb9fb334aea51c176

Observation 1ca954c3-7fbb-4e6c-af01-05b0621262f0 · inbound

AGC-Bench: Measuring Artificial General Creativity cites this paper.

AGC-Bench: Measuring Artificial General Creativity Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:36:56.051567Z

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=arxiv_source observed=2026-07-02T12:33:53.029578Z digest=sha256:e1495aff290d7ca741747bcbd1d573fe3d0ce20db1a07379ddd7202b64e2607b

Observation 08c71db3-2592-4c22-8b56-38fb14706716 · inbound

AGC-Bench: Measuring Artificial General Creativity cites this paper.

AGC-Bench: Measuring Artificial General Creativity Evaluating the Robustness of Analogical Reasoning in Large Language Models

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T21:28:58.095269Z

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=arxiv_source observed=2026-07-03T21:25:14.030920Z digest=sha256:00ba4ea45d1fdbd7b4bd8f0b5a50bed6ad91d17abe1bc80dca965561888d5383