Paper Citation Record · LEDGER

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models

As of 12 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2412.17821.

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

pith.paper-citation-record.v1
2412.17821 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:45:23.696582Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T17:30:09.824982Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T17:31:08.357429Z

Reference resolution

14 of 14 outbound references displayed

verified exact2
verified fuzzy2
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5ca8ae60-4937-4d40-aca7-0680bbc265cb · outbound

This paper cites A Survey on Software-Defined VANETs: Benefits, Challenges, and Future Directions.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models A Survey on Software-Defined VANETs: Benefits, Challenges, and Future Directions

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T19:45:24.025150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5e0da662-bedd-403e-b376-f02022aba473 · outbound

This paper cites BioBERT: a pre-trained biomedical language representation model for biomedical text mining.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models BioBERT: a pre-trained biomedical language representation model for biomedical text mining

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.635311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dd79577-4a9d-4ff3-b49a-b9b31c4d9707 · outbound

This paper cites Explainable Image Classification with Evidence Counterfactual.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Explainable Image Classification with Evidence Counterfactual

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.641028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f829b0e-7028-4de3-84ef-c0cc82364d62 · outbound

This paper cites Neural Unsupervised Domain Adaptation in NLP---A Survey.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Neural Unsupervised Domain Adaptation in NLP---A Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.646973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9cb792f-d1fe-4044-a49b-f3c94b391a2c · outbound

This paper cites Overcoming Catastrophic Forgetting in Neural Networks.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Overcoming Catastrophic Forgetting in Neural Networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:45:24.057380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38515bf1-749a-4f50-ac3e-67267e89a5e7 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Universal Language Model Fine-tuning for Text Classification

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.658850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8745690f-f2ae-45a4-bfb6-76a8cd4f6706 · outbound

This paper cites Expertise and Cognitive Entrenchment: A Reexamination of Cognitive Rigidity.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Expertise and Cognitive Entrenchment: A Reexamination of Cognitive Rigidity

Reference 7

Resolution: verified exact; doi, observed 2026-08-11T19:45:23.751601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1ecef265-708f-4b1c-880a-4dc4c9632c29 · outbound

This paper cites Secrecy Capacity Bounds for Visible Light Communications With Signal-Dependent Noise.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Secrecy Capacity Bounds for Visible Light Communications With Signal-Dependent Noise

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T19:45:23.937740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c97c5de-5d6a-4b7b-87e4-792081ac60dd · outbound

This paper cites Stratifying integral representations of finite groups.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Stratifying integral representations of finite groups

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.676228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb1477d0-c66a-4885-803a-7b6d49c32951 · outbound

This paper cites Language Models are Few-Shot Learners.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Language Models are Few-Shot Learners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.681354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dd95e3e-93ae-4fa1-9b31-6f9b94f846b8 · outbound

This paper cites Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:45:24.041099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d737e81-1890-4c5e-913d-8f575f94abe6 · outbound

This paper cites Anders, Krampe, Ralf Th., and Tesch-R"omer, Clemens.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Anders, Krampe, Ralf Th., and Tesch-R"omer, Clemens

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T19:45:23.691341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 102cd969-89fa-4b53-b527-953f5913dceb · outbound

This paper cites Hierarchical cognitive control and the human pre- frontal cortex: A computational model.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Hierarchical cognitive control and the human pre- frontal cortex: A computational model

Reference 13

Resolution: verified exact; raw_fallback, observed 2026-08-11T19:45:23.879010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation afdbaf98-5356-4ffc-94fa-c1406c37c0f0 · outbound

This paper cites an unresolved cited work.

The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-11T19:45:24.075462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation c75b74a8-eafc-4bfd-b5c0-53cbd4fa7338 · inbound

SAGE-32B: Agentic Reasoning via Iterative Distillation cites this paper.

SAGE-32B: Agentic Reasoning via Iterative Distillation The Rosetta Paradox: Domain-Specific Performance Inversions in Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:31:08.360001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.